Techniques for utilizing directed acyclic graphs for deployment instructions

ABSTRACT

Techniques are disclosed for utilizing directed acyclic graphs for deployment instructions. A computer-implemented method can include various operations. Instructions may be executed by a computing device to perform parses of configuration data associated with a deployment. The computing device may cause a first directed acyclic graph (DAG) to be generated, the first DAG being utilized for deploying a first resource based on the parses. A second DAG may be generated for deploying execution targets based on the parses, the second DAG specifying dependencies between execution targets of the deployment. The computing device may generate a linked list data structure based on the parses and may deploy the computing system by traversal of the linked list data structure.

The present application is a non-provisional application of, and claimsthe benefit and priority under 35 U.S.C. 119(e) of the following U.S.Provisional Applications, the entire contents of which are incorporatedby reference for all purposes:

U.S. Provisional Application No. 62/963,335, filed Jan. 20, 2020,entitled “TECHNIQUES FOR DEPLOYING INFRASTRUCTURE RESOURCES WITH ADECLARATIVE PROVISIONING TOOL”;

U.S. Provisional Application No. 62/963,413, filed Jan. 20, 2020,entitled “TECHNIQUES FOR DETECTING DRIFT IN A DEPLOYMENT ORCHESTRATOR”;

U.S. Provisional Application No. 62/963,456, filed Jan. 20, 2020,entitled “USER INTERFACE TECHNIQUES FOR AN INFRASTRUCTURE ORCHESTRATIONSERVICE”;

U.S. Provisional Application No. 62/963,477, filed Jan. 20, 2020,entitled “TECHNIQUES FOR UTILIZING DIRECTED ACYCLIC GRAPHS FORDEPLOYMENT INSTRUCTIONS”;

U.S. Provisional Application No. 62/963,478, filed Jan. 20, 2020,entitled “TECHNIQUES FOR RESOLVING APPLICATION UPDATES”;

U.S. Provisional Application No. 62/963,480, filed Jan. 20, 2020,entitled “TECHNIQUES FOR MANAGING DEPENDENCIES OF AN ORCHESTRATIONSERVICE”;

U.S. Provisional Application No. 62/963,452, filed Jan. 20, 2020,entitled “TECHNIQUES FOR ROLLBACK OF AN INFRASTRUCTURE ORCHESTRATIONSERVICE”;

U.S. Provisional Application No. 62/963,486 filed Jan. 20, 2020,entitled “TECHNIQUES FOR DEPLOYING INFRASTRUCTURE COMPONENTS IN PHASES”;

U.S. Provisional Application No. 62/963,489, filed Jan. 20, 2020,entitled “TECHNIQUES FOR MANAGING LONG-RUNNING TASKS WITH A DECLARATIVEPROVISIONER”;

U.S. Provisional Application No. 62/963,481, filed Jan. 20, 2020,entitled “TECHNIQUES FOR TRANSFERRING DATA ACROSS AIR GAPS”; and

U.S. Provisional Application No. 62/963,491, filed Jan. 20, 2020,entitled “TECHNIQUES FOR PREVENTING CONCURRENT EXECUTION OF DECLARATIVEINFRASTRUCTURE PROVISIONERS”.

BACKGROUND

Today, cloud infrastructure services utilize many individual services toprovision and deploy code and configuration (respectively) across thecloud infrastructure service's many regions. These tools requiresignificant manual effort to use, especially given that provisioning isgenerally declarative and deploying code is imperative. Additionally, asthe number of service teams and regions grows, the cloud infrastructureservice will need to continue to grow. Some cloud infrastructureservice's strategies of deploying to a larger number of smaller regionsincludes per-region expenditures, which may not scale well.

BRIEF SUMMARY

Techniques are disclosed for utilizing directed acyclic graphs fordeployment instructions. In some embodiment, a computer-implementedmethod can include various operations. Instructions may be executed by acomputing device to perform parses of configuration data associated witha deployment. The computing device may cause a first directed acyclicgraph (DAG) to be generated, the first DAG being utilized for deployinga first resource based on the parses. A second DAG may be generated fordeploying execution targets based on the parses, the second DAGspecifying dependencies between execution targets of the deployment. Thecomputing device may generate a linked list data structure based on theparses and may deploy the computing system by traversal of the linkedlist data structure.

In other embodiments, a system is disclosed for utilizing DAGs fordeployment instructions. The system may comprise one or more processorsand one or more memories storing computer-executable instructions that,when executed by the one or more processors, configure the one or moreprocessors to perform various operations. A computing device may executeinstructions to perform one or more parses of configuration dataassociated with a deployment of a computing system. The computing devicemay cause a first DAG to be generated, the first DAG being utilized fordeploying a first resource based at least in part on performing the oneor more parses. The computing device may generate a second DAG fordeploying a plurality of execution targets based at least in part onperforming the one or more parses, the second DAG specifyingdependencies between execution targets of the deployment. The computingdevice may generate a linked list data structure based at least in parton performing the one or more parses, the linked list data structurespecifying dependencies between a plurality of deployment phases. And,the computing device may deploy the computing system based at least inpart on traversing the linked list data structure, the second DAG, andthe first DAG.

In other embodiments, a computer-readable storage medium is disclosed,for utilizing DAGs for deployment instructions, that may storecomputer-executable instructions that, when executed by one or moreprocessors, cause the one or more processors to perform variousoperations. A computing device may execute instructions to perform oneor more parses of configuration data associated with a deployment of acomputing system. The computing device may cause a first DAG to begenerated, the first DAG being utilized for deploying a first resourcebased at least in part on performing the one or more parses. Thecomputing device may generate a second DAG for deploying a plurality ofexecution targets based at least in part on performing the one or moreparses, the second DAG specifying dependencies between execution targetsof the deployment. The computing device may generate a linked list datastructure based at least in part on performing the one or more parses,the linked list data structure specifying dependencies between aplurality of deployment phases. And, the computing device may deploy thecomputing system based at least in part on traversing the linked listdata structure, the second DAG, and the first DAG.

BRIEF DESCRIPTION OF DRAWINGS

To easily identify the discussion of any particular element or act, themost significant digit or digits in a reference number refer to thefigure number in which that element is first introduced.

FIG. 1 is a block diagram of an architecture for implementing at leastsome elements of a cloud infrastructure orchestration service, accordingto at least one embodiment.

FIG. 2 is a block diagram of an architecture for implementing at leastsome elements of a cloud infrastructure orchestration service, accordingto at least one embodiment.

FIG. 3 is a flow diagram for illustrating an example flock, according toat least one embodiment.

FIG. 4 is a flow diagram for illustrating an example flock, according toat least one embodiment.

FIG. 5 is a user interface that presents information related to arelease including multiple phases and multiple execution targets,according to at least one embodiment.

FIG. 6 is an example code segment for defining a list and order ofphases, according to at least one embodiment.

FIG. 7 is an example data structure that may be generated by a cloudinfrastructure orchestration service (CIOS) to maintain a list and orderassociated with one or more phases, according to at least oneembodiment.

FIG. 8 is an example code segment for defining a list and order ofexecution targets, according to at least one embodiment.

FIG. 9 is an example data structure that may be generated by a cloudinfrastructure orchestration service (CIOS) to maintain a list and orderassociated with one or more execution targets associated with a phase,according to at least one embodiment.

FIG. 10 is an example code segment for establishing explicit andimplicit dependencies between resources of an execution target,according to at least one embodiment.

FIG. 11 is an example code segment for establishing explicit andimplicit dependencies between resources of an execution target,according to at least one embodiment.

FIG. 12 is an example directed acyclic graph corresponding to resourceof a cloud-computing system, according to at least one embodiment.

FIG. 13 is a flow diagram illustrating an example process fororchestrating the execution of a task that includes a dependency on atleast one capability, according to at least one embodiment.

FIG. 14 is an example process flow of computer infrastructureorchestration service traversing a linked list, an execution targetdirected acyclic graph, and a capability directed acyclic graph,according to at least one embodiment.

FIG. 15 is a flow chart of a process for deploying a computing systemusing directed acyclic graphs in a computer infrastructure orchestrationservice, according to at least one embodiment.

FIG. 16 is a block diagram of a distributed system, according to atleast one embodiment.

FIG. 17 is a block diagram of one or more components of a systemenvironment by which services provided by one or more components of anembodiment system may be offered as cloud services, according to atleast one embodiment.

FIG. 18 is a block diagram of an example computer system, in whichvarious embodiments of the present disclosure may be implemented.

DETAILED DESCRIPTION

In some examples, infrastructure as a service (IaaS) is one particulartype of cloud computing. IaaS can be configured to provide virtualizedcomputing resources over a public network (e.g., the Internet). In someexamples, IaaS is one of the three main categories (or sub-categories)of cloud computing services. Most consider the other main categories tobe software as a service (SaaS) and platform as a service (PaaS), andsometimes SaaS may be considered a broader category, encompassing bothPaaS and IaaS, with even some considering IaaS to be a sub-category ofPaaS as well.

In an IaaS model, a cloud computing provider can host the infrastructurecomponents (e.g., servers, storage devices, network nodes (e.g.,hardware), deployment software, platform virtualization (e.g., ahypervisor layer), or the like).

In some cases, an IaaS provider may also supply a variety of services toaccompany those infrastructure components (e.g., billing, monitoring,logging, security, load balancing and clustering, etc.). Thus, as theseservices may be policy-driven, IaaS users may be able to implementpolicies to drive load balancing to maintain application availabilityand performance.

In some instances, IaaS customers may access resources and servicesthrough a wide area network (WAN), such as the Internet, and can use thecloud provider's services to install the remaining elements of anapplication stack. For example, the user can log in to the IaaS platformto create virtual machines (VMs), install operating systems (OSs) ineach VM, deploy middleware, such as databases, create storage bucketsfor workloads and backups, and install even install enterprise softwareinto that VM. Customers can then use the provider's services to performvarious functions, including balancing network traffic, troubleshootingapplication issues, monitoring performance, managing disaster recovery,etc.

In most cases, a cloud computing model will require the participation ofa cloud provider. The cloud provider may, but need not be, a third-partyservice that specializes in providing (e.g., selling) IaaS. An entitymight also opt to deploy a private cloud, becoming its own provider ofinfrastructure services.

In some examples, IaaS deployment is the process of putting a newapplication, or a new version, onto a prepared application server or thelike. It may also include the process of preparing the server (e.g.,installing libraries, daemons, etc.). This is often managed by the cloudprovider, below the hypervisor layer (e.g., the servers, storage,network hardware, and virtualization). Thus, the customer may beresponsible for handling (OS), middleware, and/or application deployment(e.g., on self-service virtual machines (e.g., that can be spun up ondemand) or the like.

In some examples, IaaS provisioning may refer to acquiring computers orvirtual hosts for use, and even installing needed libraries or serviceson them. In most cases, deployment does not include provisioning, andthe provisioning may need to be performed first.

In some cases, there are two different problems for IaaS provisioning.First, there is the initial challenge of provisioning the initial set ofinfrastructure before anything is running. Second, there is thechallenge of evolving the existing infrastructure (e.g., adding newservices, changing services, removing services, etc.) once everythinghas been provisioned. In some cases, these two challenges may beaddressed by enabling the configuration of the infrastructure to bedefined declaratively. In other words, the infrastructure (e.g., whatcomponents are needed and how they interact) can be defined by one ormore configuration files. Thus, the overall topology of theinfrastructure (e.g., what resources depend on which, and how they eachwork together) can be described declaratively. In some instances, oncethe topology is defined, a workflow can be generated that creates and/ormanages the different components described in the configuration files.

In some embodiments, IaaS provisioning may include generating a directedacyclic graph (DAG). A DAG may be a finite directed graph that includesany suitable number of nodes and edges, with each edge being directedfrom one node to another. The nodes and edges may be arranged to avoiddirected cycles. That is, the DAG is arranged such that there is no wayto start at any node and follow a consistently directed sequence ofedges that eventually loop back to that same node. IaaS provisioning mayinclude parsing configuration files corresponding to one or moreresources (e.g., services, software resources, etc.) of the system. Aseparate DAG may be generated for each resource. The DAG for eachresource may define dependencies of that resource on capabilities of oneor more other resources. A “capability” may be intended to refer to aportion of functionality of a given resource. A process may beinstantiated to traverse a DAG. When a node of the DAG is reached thatcorresponds to a capability that is currently unavailable, the processmay publish to a scheduling service an indication that the process hasreached a dependency on the capability and thus, is waiting for thatparticular capability to become available before it can proceed. Asvarious resources of the system are deployed and/or booted up theseresources may publish to a scheduling service an indication of thevarious capabilities availability as the capabilities become available.As used herein, the term “boot,” “booting,” “booted” refer to a processof performing a startup sequence of operations corresponding to aparticular resource (e.g., a software service, a computing device,etc.). Deploying a resource (e.g., a software service) can includebooting and/or otherwise making available at least some portion offunctionality provided by the resource. When the scheduling servicedetermines that the particular capability has become available, it mayrestart the process from the point at which it exited last (e.g., justafter publishing the need for the capability). The process mayregenerate the DAG and recommence traversal (e.g., from the last nodeaccessed). By utilizing the DAGs for each resource, the system maymanage capabilities between resources such that human operators are nolonger need to manually boot a complex system up.

In some examples, an infrastructure may have many interconnectedelements. For example, there may be one or more virtual private clouds(VPCs) (e.g., a potentially on-demand pool of configurable and/or sharedcomputing resources), also known as a core network. In some examples,there may also be one or more security group rules provisioned to definehow the security of the network will be set up and one or more virtualmachines (VMs). Other infrastructure elements may also be provisioned,such as a load balancer, a database, or the like. As more and moreinfrastructure elements are desired and/or added, the infrastructure mayincrementally evolve.

As noted above, one way to provision the infrastructure is to describeit declaratively. As such, the configuration file may be a declarativefile that merely describes each of the infrastructure components notedabove and how they interact. The configuration file can describe theresource and the relevant fields needed to create the element, and thenas other elements can be described that reference the previouslydescribed elements. In some examples, a provisioning tool can thengenerate a workflow for creating and managing the elements that aredescribed in the configuration file.

In some instances, the workflow of the provisioning tool may beconfigured to perform various commands. One function that can beperformed is view reconciliation, where the provisioning tool cancompare the view of the current infrastructure (e.g., the expected stateof the infrastructure) with how the infrastructure is actually running.In some instances, performing the view reconciliation function mayinclude querying various resource providers or infrastructure resourcesto identify what resources are actually running. Another function thatthe provisioning tool can perform is plan generation, where theprovisioning tool can compare the actually running infrastructurecomponents with what the provisioning tool wants the state to look like(e.g., the desired configuration). In other words, the plan generationfunction can determine what changes need to be made to bring theresources up to the most current expectations. In some instances, athird function is the execution (e.g., apply) function, where theprovisioning tool can execute the plan generated by the plan generationfunction.

In general, provisioning tools may be configured take the configurationfile, parse the declarative information included therein, andprogrammatically/automatically determine the order in which theresources need to be provisioned in order to execute the plan. Forexample, if the VPC needs to be booted before the security group rulesand VMs are booted, then the provisioning tool will be able to make thatdetermination and implement the booting in that order without userintervention and/or without that information necessarily being includedin the configuration file.

In some instances, continuous deployment techniques may be employed toenable deployment of infrastructure code across various virtualcomputing environments. Additionally, the described techniques canenable infrastructure management within these environments. In someexamples, service teams can write code that is desired to be deployed toone or more, but often many, different production environments (e.g.,across various different geographic locations, sometimes spanning theentire world). However, in some examples, the infrastructure on whichthe code will be deployed must first be set up. In some instances, theprovisioning can be done manually, a provisioning tool may be utilizedto provision the resources, and/or deployment tools may be utilized todeploy the code once the infrastructure is provisioned.

As noted above, generally there are two different tools used to handleeach of the provisioning of infrastructure resources and the deploymentsof code to control the infrastructure resources, with orchestrationbetween the two tools being performed manually. However, at scale,manual implementation always leads to deviations. Thus, an automatedtool that can both provision and deploy a virtual infrastructure enablesmore efficient and reliable techniques for implementing a virtual cloudenvironment.

In some examples, when two tools are used, issues can arise when a usermanually makes changes to the code between the provisioning phase andthe deployment phase. As described herein, a technique that uses asingle tool for both provisioning and deploying can alleviate that byautomating the process, such that there isn't an opportunity for manualcode changes. It may be the case, that a slight change to the way inwhich one user codes something, can create major issues in thedeployment phase. In some examples, the first time an operator performsan action in a new region (e.g., a typo in the code), the object thatwas coded with the typo may be that way forever. If the application isdeployed with that typo, and the application is not sensitive to thattypo (e.g., it still works), it is possible that some time down theroad, an additional code change could become sensitive to that typo, andcrash the entire system. Thus, the techniques provided herein can removethe gap between provisioning and deployment that can often lead toproblems.

In general, modeling deployments is declarative such that aconfiguration file can be used to declare the infrastructure resources.For example, create, read, update, delete (CRUD) instructions aregenerally used to generate deployment files using generalRepresentational State Transfer (REST) concepts (e.g., REST ApplicationProgramming Interfaces (APIs)). However, deployment itself doesn'tgenerally follow the same concept. Additionally, while theinfrastructure provisioning tools tend to be really powerful and/orexpressive, the tools for deployment tend to be much more restrictiveregarding the operations they can perform (e.g., they are imperative asopposed to declarative). Thus, there has been a long-felt need for atool that can handle both functional requirements (e.g., provisioningand deployment of infrastructure elements) within a cloud environment.

In some examples, techniques for implementing a cloud infrastructureorchestration service (CIOS) are described herein. Such techniques, asdescribed briefly above, can be configured to manage both provisioningand deploying of infrastructure assets within a cloud environment. Insome instances, the CIOS can include two classes of service: the Centraland Regional components (e.g., CIOS Central and CIOS Regional). Thefollowing terms will be used throughout:

-   -   Infrastructure component—A long-lived piece of infrastructure        that supports running code.        -   Examples: a deployment application, a load balancer, a            domain name system (DNS) entry, an object storage bucket,            etc.    -   Artifact—Code being deployed to a deployment application or a        Kubernetes engine cluster, or configuration information        (hereinafter, “config”) being applied to an infrastructure        component. These may be read-only resources.    -   Deployment task—A short-lived task that is often associated with        deploying or testing code. Additionally, the deployments tasks        are modeled as resources that live no longer than the release        that creates them.        -   Examples: “deploy $artifact to $environment,” “watch $alarm            for 10 minutes,” “execute $testSuite,” or “wait for            $manualApproval”        -   For example, CIOS can model a deployment orchestrator            deployment as the creation of a resource that transitions to            the Available state when it completes.        -   Because CIOS maintains the state of its cloud infrastructure            service declarative provisioner, CIOS can control the            lifecycle of these short-lived resources as it relates to            releases.    -   Resource—a CRUD'able resource.        -   CIOS models each of the constructs listed above as a            resource. The next section discusses this modeling in            detail.    -   Flock—CIOS's model encapsulating a control area and all its        components. Exists primarily to model ownership of and point at        the infrastructure components.    -   Flock config—Describes the set of all infrastructure components,        artifacts, and deployment tasks associated with a single        service.        -   Each Flock has exactly one Flock config. Flock configs are            checked in to source control.        -   Flock configs are declarative. They expect CIOS to provide            realm, region, ad, and artifact versions as input.        -   Flocks are granular—a Flock consists of a single service and            supporting infrastructure.    -   State—A point-in-time snapshot of the state of every resource in        the flock.    -   Release—A tuple of a specific version of a flock config and a        specific version of every artifact that it references.        -   Think of a release as describing a state that may not yet            exist.    -   Release plan—The set of steps that the CIOS would take to        transition all regions from their current state to the state        described by a release.        -   Release plans have a finite number of steps and a            well-defined start and end time.    -   Apply—This is a noun. A single attempt to execute a Release        plan. An Execution changes the current State of the Flock.

CIOS can be described as an orchestration layer that appliesconfiguration to downstream systems (e.g., world-wide). It is designedto allow world-wide infrastructure provisioning and code deployment withno manual effort from service teams (e.g., beyond an initial approval insome instances). The high level responsibilities of CIOS include, butare not limited to:

-   -   Providing teams with a view in to the current state of resources        managed by CIOS, including any in-flight change activity.    -   Helping teams plan and release new changes.    -   Coordinating activity across various downstream systems within a        region to execute approved release plans with no human        intervention.    -   Coordinating activity across regions/realms to execute approved        release plans world-wide.

In some examples, CIOS handles onboarding by enabling teams to provideCIOS with configuration information via checked-in code. Additionally,CIOS can automate more things, so this is a heavier-weight exercise thanin previous implementations. In some instances, CIOS handlespre-deployment by offering teams the ability to automatically deploy andtest code. In some instances, CIOS can handle the writing of changemanagement (CM) policy by enabling automatically generating plans toroll out new artifacts (e.g., world-wide) when a team builds them. Itcan do this by inspecting the current state of each region and thecurrent CIOS config (which, can itself be an artifact). Additionally,teams can inspect these plans, and may iterate on them by changing theCIOS config and asking CIOS to re-plan. Once the team is satisfied witha plan, they can create a “release” that references the plan. The plancan then be marked as approved or rejected. While teams can still writeCMs, they are just pointers to the CIOS plan. Thus, teams can spend lesstime reasoning about the plan. Plans are more accurate because they aremachine generated. Plans are almost too detailed for human consumption;however, it can be displayed via a sophisticated user interface (UI).

In some examples, CIOS can handle execution of CMs by automaticallyexecuting the deployment plan. Once release plan has been created andapproved, engineers no longer participate in CMs unless CIOS initiatesroll-back. In some cases, this may require teams to automate tasks thatare currently manual. In some examples, CIOS can handle rolling back achange management (CM) by automatically generating a plan that returnsthe flock to its original (e.g., pre-release) state when CIOS detectsservice health degradation while executing. In some examples, CIOS canhandle deploying emergent/tactical changes by receiving a release planthat is scoped to a subset of regions and/or a subset of the resourcesmanaged by CIOS, and then executing the plan.

Additionally, CIOS may support primitives necessary to define fullyautomated world-wide deployments. For example, CIOS can measure servicehealth by monitoring alarms and executing integration tests. CIOS canhelp teams quickly define roll-back behavior in the event of servicedegradation, then can execute it automatically. CIOS can automaticallygenerate and display release plans and can track approval. In someinstances, the language that teams use to describe desired deploymentbehavior may be declarative. CIOS can combine the functionality of codedeployment and infrastructure config (e.g., provisioning) in one system.CIOS also supports flexible ordering across regions, and acrosscomponents within a region. Teams can express ordering via checked-inconfig. Teams may call CIOS's planning and release APIsprogrammatically.

FIG. 1 depicts an architecture 100 for illustrating techniques forimplementing at least CIOS Central 102. In some examples, CIOS Central102 can be the service that handles operations at the level of a“Flock.” CIOS Central 102 has a few responsibilities, including but notlimited to:

-   -   Serving as an authentication gateway for Flock metadata changes        and release operations.    -   Storing an authoritative mapping of Flock metadata to the        deployment artifacts and CIOS repositories for the flock.    -   Coordinating global Releases across Phases and Targets.    -   Synchronization to enforce policies like “no more than one        ongoing release to a Flock at a time.”    -   Detecting changes to Flock configuration (config) and artifacts,        and triggering a release generation on such changes.

In some examples, a source code version-control management service(SCVMS) 104 can be configured to store authoritative Flock configurationand an artifact notification service (ANS) 106 can be subscribed to byCIOS Central 102, so that CIOS Central 102 can be informed of newartifact builds. The CIOS Central 102 can then map incoming changesagainst the affected flocks, and initiate release planning wheredesired. Additionally, in some examples, an artifact push service (APS)can be invoked by CIOS Central 102, before a release to a target, toensure any artifacts required for a successful release are present inthe target's region ahead of release.

In some examples, customers (e.g., engineers) 108 can call CIOS Central102 to CRUD flocks and/or releases, and to view the status of ongoingCIOS activity. Flock management service 110 can include one or moreAPI's to manipulate flocks, view/plan/approve service 112 can includeCRUD API's to create and approve plans, and to view a central copy ofthe state of all CIOS-managed resources, change monitoring service 114can watch SCVMS 104 for changes to flock config, and can receivenotifications about changes to other artifacts from ANS 106, and stateingester service 116 can create copies of regional state in CIOS Centraldatabase (DB) 118 so that view/plan/approve 112 can expose them. In someexamples, the CIOS Central DB 118 can be a DB of flocks, plans, andstate. Flock information can be authoritative; while everything else maybe a stale copy of data from CIOS Regional 120. CIOS Central 102 may beconfigured to provide any suitable portion and/or number of userinterfaces (e.g., user interfaces 500-1300) for presenting any suitabledata related to a flock, a release, an infrastructure component, anartifact, or the like. In some embodiments, CIOS Central 102 may presentvia any suitable interface data related to one or more releases. Arelease may include any suitable combination of tasks related to one ormore infrastructure components and/or one or more code changes to one ormore applications (e.g., artifacts). Some examples of the userinterfaces provided by CIOS Central 102 are described below with respectto FIGS. 5-13 .

In some examples, engineer 108 can perform an API call for the flockmanagement service 110 (e.g., through the ingress proxy fleet 122) tocreate a list of flocks. The protocol for making such an API call can behypertext transport protocol secure (HTTPS) or the like. Relevant accesscontrol lists (ACLs) for this operation can include a local area network(LAN) 124 or other private connection. For example, CIOS maymanage/control a network-connectivity alternative to using the publicInternet for connecting a customer's on-premises data center or networkwith CIOS (e.g., a dedicated, leased, and/or private connection).Additionally, authentication and authorization (e.g., of the engineer108) may be performed by a reservation system portal that allows usersto manage machine infrastructure (e.g., reservation service). In someinstances, CIOS Central 102 can store flock metadata, plans, and statein the Central DB 118, using Java database connectivity (JDBC) or thelike. In some examples, ANS 106 can be configured to notify the changemonitoring service 114 when new artifacts have been published. The ANS106 may use HTTPS, and both authentication and authorization may behandled by a mutual transport layer security service. Additionally, insome instances, the change monitoring service 114 can poll the SCVMS 104for flock configuration changes. This polling can be performed usingsecure shell (SSH) or other protocols. Authentication of the changemonitoring service 114 may be handled by a CIOS system account andauthorization may be handled by SCVMS 104.

In some examples, the engineer 108 can use the view/plan/approve service112 to do one or more of the following operations. The engineer 108 canplan and/or approve by calling CIOS Central 102 to generate and approveplans. The engineer 108 can view by calling CIOS Central 102 to view thestatus of ongoing CIOS activity world-wide. Additionally, the engineer108 can CIOS Central 102 to view a replica of the state of CIOS-managedresources world-wide. These API calls (or the like) can be performed viathe HTTPS protocol or similar protocols. Additionally, relevant ACLs canbe controlled by LAN 124, and both authentication and authorization canbe handled by the reservation service. In some examples, theview/plan/approve service 112 can request planning and push planapproval to all regions of CIOS Regional 120 (e.g., using HTTPS or thelike). Relevant ACLs can be controlled using a security list managed bythe wide area network (WAN) gateway 126. Authentication can be handledby mutual transport layer security and authorization can be handled byvarious identity policies. Further, the state ingester service 116 canwatch CIOS Regional 120 for job status or state changes, so that CIOScan provide a central view of them upon request (e.g., also using HTTPSor the like). ACLSs for this can also be handled by the WAN gateway 126,and both authentication and authorization can be handled by mutualtransport layer security services.

FIG. 2 depicts an architecture 200 for illustrating techniques forimplementing at least CIOS Regional 202. In some examples, CIOS Regional202 is where much of the work of declarative provisioning and planning,as well as approved release application can occur. In some instances,each instance of CIOS Regional 202 may have a regional fronted that canhandle operations at the level of “Execution Targets.” It can beconfigured to perform the following:

-   -   Handling all CIOS Authentication for incoming operations from        CIOS Central 102.    -   Enforcing a rule that only one “execution” (plan/import        resources/apply plan) can be ongoing for a given Execution        target at a time.    -   Managing binary artifact storage for declarative provisioning        artifacts used for input and output during declarative        infrastructure provisioning execution. Examples of input are        declarative infrastructure provisioning configuration files and        an input state file. Typical output is a final state file.    -   Requesting work from and polls for results from the CIOS        Executor for any given execution.

In some instances, the CIOS Frontend may be dependent on a CIOS Executor206 (also referred to herein as a “scheduler”), which can handle theactual execution. The CIOS Executor, in some examples, operates at thelevel of “Execution,” and it can:

-   -   Track a pool of available Worker nodes    -   Query incoming job requests, and assigns them to eligible        workers as available    -   Track worker status and Execution updates for reporting to        clients    -   Detect dead nodes via a leasing protocol, and can fail tasks        assigned to dead nodes, depending on task status.    -   Provide facilities to cancel/kill/pause/resume Executions, and        can map those onto facilities to pass        cancellation/kill/resumption info on to Worker nodes.

In some instances, the CIOS Executor can depend on CIOS Workers, whichcan assign tasks for execution to Workers, and provide a facility forWorkers to update job progress. The worker service operates at thegranularity of “Task.” Each worker is an agent executing Tasks assignedto that worker and reporting Task status and output. Each worker can:

-   -   Poll Executor Worker APIs for assigned work items, and take        action to make the assign state match its local state:        -   start containers for polls task items that do not exist            locally        -   kill containers for locally running containers that have no            corresponding assigned task item    -   Report status for jobs    -   Stage input and output for job container execution    -   Launch and monitor declarative infrastructure provisioning        containers for doing the real work of a Release for an Execution        Target.

CIOS Workers may depend on CIOS Executor to poll work from and reportresults to the worker endpoint of the CIOS Executor. The Worker may relyon the Executor for all coordination. Additionally, the CIOS Workers mayalso depend on CIOS Regional 202, where the Worker services reads inputfrom and writes output to one or more APIs that are associated with theRegional Frontend service. Examples of input are configuration andstarting state files and import mappings. Examples of output aredeclarative provisioning process, output declarative provisioning statefiles, and import result states.

In some examples, CIOS Regional 202 can be a regional service formanaging regional instances/deployments of CIOS. CIOS Regional 202covers responsibility for authoritatively storing and managing plans andstat that pertains to a particular region. A Regional DB 204 may be aCIOS DB for the state and plans in the particular region. This is theauthoritative copy of the region's subset of the Central DB 118 of FIG.1 . Scheduler 206 can be responsible for managing worker fleet capacity,assigning tasks to workers, and keeping track of task state. In someinstances, Task DB 208 is another CIOS DB for task state. Data in thisDB is mostly for operational purposes. Additionally, Worker 210 can be afleet of java virtual machines (JVMs) that manage declarativeprovisioning images. These receive instructions from the Scheduler 206and communicate results to both the Scheduler 206 and CIOS Regional 202.A CIOS container 212 can run declarative provisioning actions in its ownprivate docker 214 container. This container does not need to containsecrets. Additionally, in some examples, a signing proxy 216 can beconfigured to prevent secret exfiltration via a declarative provisioningtool, in order to avoid putting secrets in the declarative provisioningImage. Instead, CIOS can perform request signing or initiate a mutualtransport layer security (mTLS) service in a proxy. This also makes iteasier to use FIPS-compliant crypto libraries.

In some examples, CIOS Central 102 can call CIOS Regional 202 to createplans, push approvals, watch job status (service principal), and extractdeclarative provisioner state (service principal). An ingress proxy 218can be configured as the ACL and various identity policies may be usedfor both authentication and authorization. Alternatively, in someexamples, the ingress proxy 218 may be replaced with a load balancerconfigured to balance the load incoming requests, plans, etc. In someinstances, CIOS Regional 202 may run a declarative provisioner by askingthe scheduler 206 to do so. Worker 210 can ask Scheduler 206 what itshould be running, and can report status to Scheduler 206 when done. Insome cases, mTLS may handle both authentication and authorization forCIOS Regional 202 and Worker 210. Additionally, when Worker 210 needs torun a declarative provisioner, it does so in docker containers byinteracting with the local docker 214. Authentication for this stage maybe handled by a local unix socket. A docker protocol may be used forthis last step; however, HTTPS may be utilized for the previous ones.

In some embodiments, CIOS Regional 202 may be configured to provide anysuitable portion and/or number of user interfaces (e.g., user interfaces500-1300) for presenting any suitable data related to a flock, arelease, an infrastructure component, an artifact, or the like. In someembodiments, CIOS Regional 202 may present via any suitable interfacedata related to one or more releases. A release may include any suitablecombination of tasks related to one or more infrastructure componentsand/or one or more code changes to one or more applications (e.g.,artifacts). Some examples of the user interfaces provided by CIOSRegional 202 are described below with respect to FIGS. 5-13 .

In some examples, the CIOS container 212 enables a declarativeprovisioner to interact (via API) with the signing proxy 216, while thedeclarative provisioner thinks it's calling various CIOS services. Thesigning proxy 216 listens on one ephemeral port per calling instance ofdeclarative provisioner, known only to that declarative provisioner. Thesigning proxy 216 can initiate requests signatures or mTLS, and can passthe declarative provisioner's calls through to other CIOS serviceswithin the service enclave. In some instances, the signing proxy 216 canalso communicate with one or more public CIOS services 220. For example,the Signing Proxy 216 will use the internal endpoint of public serviceswhere possible. For services with no internal endpoint, it must use theegress proxy 222 to reach the external endpoint. This use of the signingproxy 216 may not be for cross-region communication; for example, anegress proxy whitelist in each region may only be for that region'spublic IP ranges. In some examples, Worker 210 may then persist stateand logs from a declarative provisioner in CIOS Regional 202 so thatthey can be exfiltrated to CIOS Central 102.

Using CIOS, there are a few phases of a representative customerexperience: onboarding, pre-release, world-wide release, and tacticalrelease. For the pre-release phase, the below is an example of whathappens between a new artifact being built and releasing artifacts torelease one (e.g., R1). This should replace some or most of currentchange management processes. As relevant artifacts are built, CIOS canautomatically generate releases using “the latest version of everythingin the flock.” A release is a specific version of the flock config withspecific inputs (e.g. artifact versions, realm, region, and ad). Arelease contains one roll-forward plan per region and metadatadescribing region ordering. Each regional plan is the set of operationsa declarative provisioner would take to realize the flock configurationin that region. Teams with pre-release environments can use CIOS toautomatically release and test software in said environments. Teams canconfigure CIOS to automatically test the roll-back plan. Teams will beable to inspect and approve releases through the CIOS UI. Teams canapprove some but not all of the regional plans within a release. If “thelatest version of everything” yielded no suitable plans, teams can askCIOS to generate a plan for cherry-picked artifact versions.

For the world-wide release phase, the below is an example of how a teamexecutes tomorrow's version of today's “normal CM.” Once a release isapproved, CIOS pushes each approved regional plan to the respectiveregion. CIOS acts independently within each region to apply approvedplans. CIOS will only perform the set of actions explicitly described inthat region's plan. Instead of “thinking independently,” it will fail.CIOS UI shows teams the progress of the execution. CIOS UI prompts teamswhen manual approvals are required. If execution fails because of anoutage in CIOS or in a downstream service, CIOS can notify the team andcan prompt them for next steps (e.g., abort, retry). CIOS does performretries, but some downstream system outages will exceed its willingnessto retry. If execution fails because of service health degradation or atest failure, CIOS will assist teams with rolling the flock back to itsstarting state. CIOS will notify (e.g., page) teams when it initiatesautomatic rollback. Teams must approve the roll-back plan, then CIOSwill execute it.

For the tactical release phase, the below is an example of how a teamcan execute tomorrow's version of an “emergent CM.” When generating aplan, teams may ask CIOS to target the plan at specific resources inseveral ways: topologically (e.g., realm, region, AD, etc.), by resourcetype (e.g., “only metrics configs” or “only deployment orchestrationservice deployments”, etc.), or combinations of the above (e.g., in adisjunctive manner). Teams approve tactical releases just likeworld-wide releases. CIOS orchestrates them similarly. If a team needsto deploy a tactical release while there is an active a world-widerelease, CIOS will stop executing the world-wide release in the targetedregions, then start executing the tactical release.

In some examples, a declarative provisioner's state (e.g., traditionallya file) is an authoritative record of the set of resources managed bythe declarative provisioner. It contains the mapping between the logicalidentifier of each resource from the configuration file and the actualidentifier of the resource. When the declarative provisioner is creatinga resource, certain kinds of failure can prevent the actual identifierfrom being recorded in the state. When this happens, the actualidentifier is lost to the declarative provisioner. These can be called“orphaned resources.”

For most resources, orphans represent waste—the declarative provisionerlaunched (for example) an instance that it forgot about, but will launchanother instance instead the next time it is run. For resources withuniqueness constraints or client-supplied identifiers, orphans preventthe declarative provisioner from making forward progress. For example,if the declarative provisioner creates a user ‘nglass’ and a failureorphans it, the next run of the declarative provisioner will attempt tocreate ‘nglass’ and fail because a user with that username alreadyexists. In some cases, orphans are only a problem when adding newresources to the state. In some instances, the declarative provisioner'srefresh behavior may naturally recover from failures to record updatesand deletions.

CIOS needs to be robust in the event of downstream service outages oroutages of CIOS itself. Because CIOS can leverage a declarativeprovisioner to apply changes, this means there should be robustnessaround running the declarative provisioner and maintaining thedeclarative provisioner state. The declarative provisioner providersperform ‘small scale’ retries—enough to avoid outages lasting for smallnumbers of minutes. For example, a cloud provider will retry for up to30 minutes. Downstream system outages lasting longer than 30 minuteswill cause the declarative provisioner to fail. When the declarativeprovisioner fails, it records all changes it successfully made in thestate, then exits. To retry, CIOS must re-execute the declarativeprovisioner. Re-executing the declarative provisioner also allows CIOSto retry in the event of a failure in CIOS itself. In some instances,CIOS can run the following operations in a loop:

-   -   Refresh—the declarative provisioner calls GET APIs to retrieve a        fresh snapshot of every resource described in its state.    -   Plan—the declarative provisioner generates a plan (a concrete        set of API calls) that will realize the desired state, given the        recently-refreshed current state.    -   Apply—the declarative provisioner executes the set of steps in        the plan.

CIOS may always run all three of these steps when executing thedeclarative provisioner. The refresh operation helps recover from anyupdates or deletions that weren't recorded. CIOS inspects the result ofthe plan operation and compares it to the approved release plan. If thenewly generated plan contains operations that were not in the approvedrelease plan, CIOS may fail and may notify the service team.

FIG. 3 depicts a directed acyclic graph (DAG) 300 for illustrating anexample flock 302. The progression of code/config from check-in toproduction, for a single flock config in CIOS, can be described all theway from the first testing deployment to the last prod deployment.Internally, CIOS calls each element in the progression an ExecutionTarget (ET)—this is all over our internal APIs, but does not leak out into the flock config. CIOS executes ETs based on the DAG 200 defined inthe flock config. Each ET (e.g., ET-1, ET-2, ET-3, ET-4, ET-5, ET-6, andET-7) is, roughly, one copy of the service described by the flockconfig.

FIG. 4 depicts a DAG 400 for illustrating and example flock 402. In theflock config, CIOS is very opinionated about how teams express thisprogression—they must model it using cloud infrastructure tenancies andregions. Teams should not model progression using realms. CIOS allowsteams to use many tenancies within a realm and many regions within atenancy. However, CIOS does not allow teams to use the same region twicewithin a tenancy (though they may use the same region twice within arealm—in different tenancies). DAG 400 illustrates a version of DAG 300from FIG. 3 , expressed with tenancies and regions. This example is foran overlay service, where pre-prod ETs are in a prod region. A serviceenclave service would have the unstable and stable tenancies in releaseone. In DAG 400, IAD is a regional airport code for Dulles airport inWashington, D.C., YYZ is a regional airport code for Toronto, Ontario,PHX, LHR, and FRA, are regional airport codes for Phoenix, London, andFrankfurt, respectively, and LUF and LFI are for two different air forcebases.

In one embodiment, CIOS and/or other techniques described herein are animprovement on each of Terraform (a declarative provisioning tool),Tanden (a code generation tool), and the Oracle Deployment Orchestrator(ODO). Additionally, in some examples, CIOS and/or other techniquesdescribed herein can be implemented using at least portions of theTerraform, Tanden, and ODO tools.

FIG. 5 is a user interface (UI) 500 that presents information related toa release including multiple phases and multiple execution targets,according to at least one embodiment. The UI 500 may include a phasearea 502 and an execution target area 504. The phase area 502 mayindicate an ordered list of phases, such as phase 506 (e.g., “R_n”),phase 507 (e.g., “R_s”), phase 508, (e.g., “R_e”), and phase 509 (e.g.,“R_w”). In some embodiments, the phase order may be depicted from leftto right where the leftmost phase is to be completed before the phase toits right is completed, which in turn, is to be completed before thephase to its right, etc. In some embodiments, the ordered list of phasesmay be stored in any suitable data structure such as a linked list. Anexample linked list is discussed in more detail below in connection withFIG. 7 .

Each phase may be associated with a number of tasks (e.g., tasksincluding deploying one or more infrastructure resources to one or moreexecution targets). The list of phases as illustrated in the UI 500includes four phases, but any suitable number of phases may be includedin the phase area 502 for deploying infrastructure resources at one ormore execution targets. In some embodiments, the ordered list of phasespresented within phase area 502 may be horizontally scrollable. Thephase area 502 may indicate a total number of phases 510, a status 511,a number of completed and/or total number of execution targets 513, anda flock configuration identifier 514. The total number of phases 510 mayindicate a total number of phases included in the linked list and thestatus 511 may indicate a status of the release (e.g., a release thatincludes. As illustrated in FIG. 5 , the status 511 is “applying,” butthe status 511 may be any suitable status indicator (e.g. “Not Started,”“Completed,” “Failed,” etc.). As depicted in FIG. 5 , the number ofcompleted and/or total number of execution targets 513 indicates 24deployments to execution targets have been completed out of 57 totalexecution targets. The number of completed and/or total number ofexecution targets 512 may be presented on the UI 500 in any suitablemanner. The flock configuration identifier 514 is presented on the UI500 as “13380fb2832,” but the flock configuration 514 may be presentedon the UI 500 in any suitable manner for conveying a unique identifierfor the flock configuration file corresponding to the release depictedin FIG. 5 .

Each subarea corresponding to a phase may include a phase identifier(e.g., phase identifier 516), a total execution target indicator (e.g.,total execution target indicator 518), timestamp information (e.g.,timestamp information 520, an execution target tracker area (e.g.,execution target tracker area 522), and any other suitable informationrelating to the phase. For example, identifier 516 (e.g., “R_s”) may beany suitable alphanumeric string for uniquely identifying a phase. Insome embodiments, an total execution target indicator 518 may bepresented adjacent to the identifier 516. The total execution targetindicator 518 indicates a number of total execution targets (e.g., 14)that are associated with the given phase.

The timestamp information 520 may include a start time and/or an endtime associated with a time when the phase was started and/or completed,respectively. In some embodiments, the timestamp information 520 mayinclude any suitable indicator (e.g., “not started,” failed,”“completed,” etc.) for indicating a status of the corresponding phase.In some embodiments, any suitable information related to the phase maybe depicted in phase area 502. The information related to each phase maybe similarly presented or the presentation of the phase information maybe formatted differently and/or may include more or less informationthan that depicted in FIG. 5 .

An execution target tracker area (e.g., execution target tracker area522 of the phase 506) may be presented within each phase. The executiontarget tracker area of each phase may include one or more executiontarget indicators (e.g., execution target indicators 524, 526, and 528).Each execution target indicator may include a number indicating a numberof tasks (e.g., deployments to corresponding execution targets) are tobe concurrently executed. By way of example, execution target indicator524 indicates a deployment to a particular execution target may beexecuted. The execution target indicator 526 and its placement to theright of the execution target indicator 524 indicates that anotherdeployment to a different execution target is to be executed after thecompletion of the first task corresponding to execution target indicator524. The execution target indicator 528 and its placement to the rightof the execution target indicator 526 indicates that 12 separatedeployments to 12 different execution targets are to be executed afterthe completion of the second task corresponding to execution targetindicator 524. The combination of execution target indicator 524, 526,and 528, collectively depict a collapsed form of a directed acyclicgraph (e.g., DAG 900 discussed below in connection with FIG. 9 ).

In some embodiments, the execution target indicators 524-528 maycorrespond to a data structure configured to maintain the list ofexecution targets associated with a phase an order by which tasks (e.g.,deployments to each execution target) are to be executed. An exampledata structure for maintaining this list and order is described in moredetail in connection with FIG. 9 . Each execution target indicator mayinclude a ring (e.g., ring 530). The ring may be divided into anysuitable number of portions corresponding to the number of executiontargets associated with the execution target indicator. In the exampledepicted, the ring 530 may be divided into 12 equal portions. Eachportion of the ring 530 may correspond to a particular execution targetand may be colorized with a color corresponding to a status of the taskcorresponding to that particular execution target. By way of example,ring 530 may indicate (e.g., via nine green portions) that ninedeployments to execution targets have been completed. The remainingthree portions of ring 530 (e.g., colored white) may indicate threetasks corresponding to three execution targets have not yet beenstarted. As another example, the remaining three portions of ring 530may be colored a different color (e.g., yellow) indicating thatcorresponding tasks have been started but have yet to be completed.Thus, by looking at the ring 530, the user is able to quickly andvisually identify a current status with the tasks associated withexecution target indicator 528. By viewing the execution targetindicators within execution target tracker area 522, the user canascertain that deployment to 11 execution targets is complete and threeare in progress. In some embodiments, each execution target indicatormay correspond to a node of a directed acyclic graph (DAG) (e.g., theDAG 900 of FIG. 9 ) that is associated with the given phase (e.g.,“R_s”).

The execution target area 504 may include an execution target column532, a progress column 534, and an operations column 536. The executiontarget column 532 may include a list of targets (e.g., executiontargets) corresponding to tasks (e.g., deployments) executed inconnection with a given phase (e.g., as depicted, phase 506). In someembodiments, the execution target column 532 may be sorted by chronologyor any other suitable method for sorting task execution. The progresscolumn 534 may include a list of progress indicators indicating status(e.g., “succeeded,” “not started,” “in progress,” etc.) corresponding toeach execution target. The operations column 536 may include a list ofoperations to be executed with respect to the given execution targetsindicated in the execution target column 532. For example, the list ofoperations included in the operations column 536 may include create,read, update, and delete (CRUD) operations or the like.

FIG. 6 is an example code segment 600 for defining a list and order ofphases, according to at least one embodiment. As illustrated in FIG. 6 ,four phases are defined in code segment 600. Each phase is defined as aresource of type “phase” and assigned an identifier (e.g., “R_n,” “R_s,”“R_e,” and “R_n”). As illustrated in the code segment 600, the resources602, 604, 606, and 608 correspond with the respective phases. Each phasemay include one or more variables one of which may include an indicatorfor indicating an execution order for each phase. In some embodiments,the indicator may indicate a dependency and/or lack of dependency on oneor more other phases. By way of example, the indicator 618 (e.g.,predecessors=[ ] at line 5) may indicate a lack of dependency on anyother phase. This can be interpreted by the system as defining a firstphase to be executed. The indicator 620 (e.g.,predeceesors=[phase.R_n.variable 1]) may be utilized to indicate adependency on another phase (e.g., phase “R_n”) through inclusion of anassignment of a value corresponding to a variable associated withanother phase (e.g., phase “R_n”). Similarly, indicator 622 may indicatea dependency on another phase (e.g., phase “R_s” through inclusion of anassignment of a value corresponding to a variable associated with “R_s”)and indicator 624 may indicate a dependency on yet another phase (e.g.,phase “R_e” through inclusion of an assignment of a value correspondingto a variable associated with “R_e”).

In some embodiments, code segment 600 may be included in a configurationfile corresponding to a release. The configuration file may beparsed/traversed one or more times as part of executing a preprocessingprocedure. In one of these traversals, the code segment 600 may beanalyzed to generate a data structure with which the identity and orderof execution corresponding to one or more phases may be maintained. FIG.7 depicts one example data structure (e.g., a linked list) which may beutilized to maintain this information.

The indicators 618-624 may be utilized to establish the specific orderby which phases are to be executed. For example, as depicted in FIG. 6 ,phase “R_n” is to be executed first, followed by phase “R_s”, followedby phase “R_e”, followed by phase “R_w”. It should be appreciated that adependency may indicate one or more other phases which are to becompleted before tasks associated with a given phase commence. Althoughfour phases are defined in FIG. 6 , it should be appreciated that anysuitable number of phases may be defined in a similar manner.

FIG. 7 is an example data structure (e.g., linked list 700) generated bya cloud infrastructure orchestration service (CIOS) to maintain a listand order associated with one or more phases. Linked list 700 may begenerated to identify the phases and execution order as defined in thecode segment 600 of FIG. 6 . As illustrated in FIG. 7 , the linked list700 includes four nodes 702, 704, 706, and 708 that may each correspondto a phase of the four phases defined in code segment 600. Each node ofthe linked list may correspond to a data object that is configured tostore any suitable information corresponding to a given phase. By way ofexample, a given node may store any suitable number of variables,identifiers, data structures, pointers, references, etc. correspondingto a particular phase. As a non-limiting example, the node 702,corresponding to phase “R_n” may store the three variables defined incode segment 600 as corresponding to the phase “R_n.” Each node oflinked list 700 may include any suitable number of variablescorresponding to a given phase.

Each node of the linked list may include a pointer/reference to anothernode in the linked list (in scenarios in which there are multiplephases). By way of example, node 702 may include a reference to node704, which may include a reference to node 706, which may include areference to node 708, which may indicate (e.g., via a null pointer)that it is the end node of the linked list 700. In some embodiments,these pointers/references may be identified based on the indicators618-624 of code segment 600.

In some embodiments, at execution time, the CIOS may identify an orderby which particular phases are to be executed based at least in part ontraversing the linked list 700 starting at node 702 (e.g., a startingnode). Execution of these phases may utilize any suitable combination ofthe data stored within each corresponding node. Upon completingoperations corresponding to a given phase, CIOS may traverse to the nextphase, repeating this process any suitable number of times untiloperations corresponding to an end node of the linked list 700 (e.g.,node 708) have been completed. In some embodiments, if the operations ofa given node are unsuccessful (e.g., produce an error), CIOS may nottraverse to the next node and may instead stop deployment and return anotification to alert the user of the situation.

Each node of the linked list 700 may correspond to a data structureconfigured to identify and maintain an execution order corresponding toone or more execution targets. FIGS. 8 and 9 discuss in more detail thedefinition and use of such a data structure. It should be appreciatedthat the linked list 700 may provide the information utilized by the UI500 of FIG. 5 to present any suitable information associated with aphase (e.g., identifier 516, time stamp information 520, executiontarget 518, etc.).

FIG. 8 is an example code segment 800 for defining a list and order ofexecution targets (e.g., execution targets corresponding to a particularphase), according to at least one embodiment. As illustrated in FIG. 8 ,four execution targets are defined in code segment 800. Each executiontarget is defined as a resource of type “execution target” and assignedan identifier (e.g., “us-la,” “us-sj,” “us-sf,” and “us-sd”). Asillustrated in the code segment 800, the resources 802-808 eachcorrespond with a unique execution target. Each execution target may beassociated with one or more variables one of which may include anindicator for indicating an execution order for each phase. In someembodiments, the indicator may indicate one or more dependencies and/orlack of dependency on one or more other execution targets. By way ofexample, the indicator 818 (e.g., predecessors=[ ] at line 5) mayindicate a lack of dependency on any other phase. This can beinterpreted by the system as defining a first execution target. Theindicator 620 (e.g., predeceesors=[execution target.us-la.variable 1])may be utilized to indicate a dependency on another execution (e.g.,phase “us-la”) through inclusion of an assignment of a valuecorresponding to a variable associated with another execution target(e.g., execution target “us-la””). Similarly, indicator 822 may indicatea dependency on another phase (e.g., execution target “us-sj” throughinclusion of an assignment of a value corresponding to a variableassociated with execution target “us-sj”) and indicator 624 may indicatea dependency on yet another phase (e.g., execution target “us-sf”through inclusion of an assignment of a value corresponding to avariable associated with execution target “us-sf”).

In some embodiments, code segment 800 may be included in a configurationfile (e.g., the same or different configuration file that includes thecode segment 800) corresponding to a release. The configuration file maybe parsed/traversed one or more times as part of executing apreprocessing procedure. In one of these traversals, the code segment800 may be analyzed to generate a data structure with which the identityand order of execution targets corresponding to a given phase may bemaintained. FIG. 9 depicts one example data structure (e.g., a directedacyclic graph (DAG)) which may be utilized to maintain this information.

The indicators 818-824 may be utilized to establish the specific orderby which execution targets are to be executed. For example, as depictedin FIG. 8 , tasks associated with execution target “us-la” are to beexecuted first, followed by tasks associated with execution target“us-sj”, followed by tasks associated with execution target “us-sf”,followed by tasks associated with execution target “us-sd”. It should beappreciated that a dependency may indicate one or more other executiontargets for which corresponding tasks are to be completed before tasksassociated with a given execution target commences. Although fourexecution targets are defined in FIG. 8 , it should be appreciated thatany suitable number of phases may be defined in a similar manner. Insome embodiments, execution targets may share a common dependency (e.g.,identical predecessors definitions). A common dependency may be utilizedto indicate that tasks associated with execution targets that share thecommon dependency may be executed concurrently.

FIG. 9 is an example data structure (e.g., a directed acyclic graph(DAG) 900) that may be generated by a cloud infrastructure orchestrationservice (CIOS) to maintain a list and order associated with one or moreexecution targets associated with a phase, according to at least oneembodiment, according to at least one embodiment. The DAG 900 may be oneof multiple DAGs generated in response to one or more parses by CIOS ofa configuration file associated with the release. Each node of the DAG900 may correspond with a single execution target. As illustrated inFIG. 9 , the DAG 900 includes six nodes (e.g., nodes 902, 904, 906, 908,910, and 912) that may each correspond to one of six execution targetsdefined in a similar manner as described with respect to code segment800 of FIG. 8 . Each node of the DAG 900 may correspond to a data objectthat is configured to store any suitable information corresponding to agiven execution target. By way of example, a given node may store anysuitable number of variables, identifiers, data structures, pointers,references, etc. corresponding to a particular execution target.

Each node of the DAG 900 may include a pointer/reference to one or morenodes in the DAG 90). By way of example, node 902 may include areference to node 904, which may include references to nodes 906-910,which each may include a reference to node 912, which may indicate(e.g., via a null pointer) that it is the end node of the DAG 900. Insome embodiments, these pointers/references may be identified based onindicators similar to indicators 818-824 discussed above in connectionwith FIG. 8 . In some embodiments, nodes 906, 908, and 910 may share acommon dependency to node 904, thus the tasks associated with the nodes906-910 may be executed, at least in part, concurrently. In someembodiments, node 912 may correspond to an execution target that dependson nodes 906-910. Thus, tasks associated with the execution targetcorresponding to node 912 may be executed only after tasks associatedwith all of the execution targets corresponding to nodes 906-910 havebeen completed.

In some embodiments, DAG 900 may be associated with a single node of thelinked list 700 discussed above in connection with FIG. 7 . That is, oneor more execution targets (e.g., identified and represented by the nodesof DAG 900) may be associated with a particular phase (e.g., a singlenode) of linked list 700. In some embodiments, the node of linked list700 may include a reference to DAG 900, or one or more nodes of DAG 900may include a reference to a node of the linked list 700.

In some embodiments, the CIOS may traverse the configuration file (e.g.,including code segment 800 of FIG. 8 ) and generate DAG 900 from thistraversal. The generation of DAG 900 may be completed as part of apreprocessing procedure executed before run time or at run time. Uponcompleting operations corresponding to a given execution target, CIOSmay traverse to the next execution target(s), repeating this process anysuitable number of times until operations corresponding to one or moreend nodes of the DAG 900 (e.g., node 912) have been completed. In someembodiments, if the operations corresponding to a given node areunsuccessful (e.g., produce an error), CIOS may not traverse to the nextnode and may instead return a notification to alert the user of thesituation.

Each node of the DAG 900 may correspond to a data structure configuredto identify and maintain an execution order corresponding to one or moreresources (e.g., services, software modules, etc.). FIGS. 10-12 discussin more detail the definition and use of such a data structure (e.g., aDAG of Capabilities). By way of example, each node of the DAG 900 maycorrespond to another DAG (e.g., DAG 1200 of FIG. 12 , indicating a listand an order of resources and/or capabilities, identifying an order oftask execution). It should be appreciated that the DAG 900 may providethe information utilized by the UI 500 of FIG. 5 to present any suitableinformation associated with the execution target indicators 524-528.Thus, the information depicted in execution target tracking area 522 maydepict a simplified version of the DAG 900 (a DAG corresponding to agiven phase, such as phase “R_s”). A simplified version of the DAG maycondense concurrently executable nodes of the DAG 900 into a single node(e.g., see execution target indicator 528 depicting 12 nodes of a DAGcondensed into a single node). In some embodiments, CIOS may deployinfrastructure resources and/or release software artifacts based atleast in part on traversing the DAG 900. The specific tasks and order oftasks are identified as described in connection with FIGS. 10-12 .

FIG. 10 is an example code segment 1000 for establishing explicit andimplicit dependencies between resources of an execution target,according to at least one embodiment. The code segment 1000, as depictedin FIG. 10 , includes two modules 1002 and 1004 and a resource 1006. Themodules 1002 and 1004 each include names 1008 and 1010 that are shown,respectively, as “apps_example1,” and “apps_example 2.” A module mayinclude a name of any suitable length including any suitablealphanumeric character(s). The modules 1002 and 1004 may defineapplications/services that a user desires to boot or otherwiseprovision. The modules 1002 and 1004 may be used to deploy applicationsto availability domain 1 and to availability domain 2, respectively. Theresource 1006 can include a multi-parameter list including a resourcetype 1012 that is shown in FIG. 10 as “type,” and a resource name 1014that is shown in FIG. 10 as “executor”. The resource type 1012 may beany type suitable for a deployment, and the resource name 1014 may beany name.

The resource 1006 may be a capability and may include an implicitdependency, an explicit dependency, or both. As depicted in the codesegment 1000, the resource 1006 attempts to assign variable “variable1”to a value equal to “module.apps_example1.variable1,” a value accessiblevia the apps_example1 module (e.g., module 1002). This is intended todepict an implicit dependency that is formed between the resource 1006and the module 1002. The formed implicit dependency may prevent theresource 1006 from executing before the module 1002 has completeddeployment. A process responsible for booting the resource 1006 mayreceive a notification that the module 1002 has completed deployment.The notification may be transmitted by a scheduler (e.g. the scheduler206 of FIG. 2 ) and may be received by the process responsible forbooting resource 1006. The formed implicit dependency is consideredimplicit since the resource 1006 as shown in FIG. 10 does not directlydefining a dependency between the module 1002 and the resource 1006.

In contrast, the resource 1006 includes an explicit dependency at line29 of FIG. 10 which includes explicitly defining a dependency betweenresource 1006 and the app_example 2 module. As depicted in the codesegment 1000 at line 29, the resource 1006 includes“depends_on=apps_example 2.variable2.” Based on the code at line 29, anexplicit dependency may be formed, and the explicit dependency mayprevent the resource 1006 from being deployed until apps_example2 hassuccessfully deployed. Upon successful deployment of apps_example 2, anotification may be transmitted by the scheduler and may be received bya process responsible for deploying the resource 1006. While the codesegment 1000 of FIG. 10 includes one resource 1006 that includes oneimplicit dependency and one explicit dependency, it should beappreciated by one of ordinary skill that any combination of resources1006, implicit dependencies, and explicit dependencies may be used toachieve a goal of a user of CIOS.

CIOS (or a declarative infrastructure provisioner such as thedeclarative provisioning tool of CIOS, discussed above) may be utilizedto parse the configuration file including code segment 1000. Throughthis parse, CIOS (or the declarative provisioning provisioner) maygenerate a directed acyclic graph (DAG) for each resource, module,and/or capability that compiles and defines an ordered list ofdependencies on other resources, modules, and/or capabilities. Whileattempting to deploy a resource, CIOS may traverse the DAG to identifywhen a resource is dependent on another resource, module, and/orcapability. The DAG for each resource may specify implicit dependencies,explicit dependencies, or a combination thereof and may be used forbooting or otherwise deploying the corresponding resource with CIOS.

FIG. 11 is an example code segment 1100 for establishing explicit andimplicit dependencies between resources of an execution target,according to at least one embodiment. The code segment 1100 asillustrated in FIG. 11 includes four resources 1102, 1104, 1106, and1108. Each resource of the resources 1102, 1104, 1106, and 1108 maycorrespond to a capability and may include implicit dependencies,explicit dependencies, or a combination thereof.

The resource 1102 as shown in FIG. 11 includes a name 1110, shown as“object_storage,” a type 1112, shown as “type1,” (e.g., indicating theresource is a capability) and a number of variables (e.g., variables1-3, although more or fewer variables may be utilized). The resource1104 as shown in FIG. 11 includes a name 1116, shown as “worker,” and anexplicit dependency 1118, shown as “depends_on=type1.object storage.”The parameter list of resource 1102 includes an identifier 1115 whichmay be used to refer to that resource (or the name 1110 may be utilizedsimilarly). The statement 1118 forms an explicit dependency on resource1102 due to the reference to type1.object storage. This explicitdependency may prevent the resource 1104 from being deployed until theresource 1102 completes deployment. The resource 1106 as shown in FIG.11 includes an identifier 1120, shown as “peacock,” a type (e.g.,“type1” indicating a capability) and a number of variables (e.g.,variable1 and variable2). The resource 1108 as shown in FIG. 11 includesa type (e.g., “type4”), a name 1124, shown as “LB,” and statement 1126(“count=type1.peacock.exists.”). The use of statement 1126 may form animplicit dependency on resource 1106. Although resource 1108 does notuse the explicit dependency construct (e.g., “depends_on”), an implicitdependency none-the-less exists due to an attempt to assign the variable“count” a value equal to whether the capability “peacock” exists (asdetermined from the statement type1.peacock.exists). Thus, the resource1108 may not be deployed until the resource 1106 “peacock” deploys dueto the assignment attempted at line 18. While the code segment 1100 ofFIG. 11 includes four resources 1102, 1104, 1106, and 1108, whichinclude one implicit dependency and one explicit dependency, it shouldbe appreciated by one of ordinary skill in the relevant art that anycombination of resources, implicit dependencies, and explicitdependencies may be used to achieve a goal of a user of CIOS.

CIOS (or a declarative infrastructure provisioner such as thedeclarative provisioning tool of CIOS discussed above) may be utilizedto parse the configuration file including code segment 1100. Throughthis parse, CIOS (or the declarative provisioning provisioner) maygenerate a directed acyclic graph (DAG) for each resource, module,and/or capability that compiles and defines an ordered list ofdependencies on other resources, modules, and/or capabilities. Whileattempting to deploy a resource, CIOS may traverse the DAG to identifywhen a resource is dependent on another resource, module, and/orcapability of another resource. The DAG for each resource may specifyimplicit dependencies, explicit dependencies, or a combination thereofand may be used for booting or otherwise deploying the correspondingresource with CIOS.

FIG. 12 is an example directed acyclic graph (DAG) 1200 corresponding toresource (e.g., resource A) of a cloud-computing system, according to atleast one embodiment. As depicted, the DAG 1200 may be a finite directedgraph that includes any suitable number of nodes (e.g., six nodes asshown in FIG. 12 ) and edges (e.g., seven edges as shown in FIG. 12 ),with each edge being directed from one node to another as depicted inFIG. 12 . The nodes and edges may be arranged to avoid directed cycles.That is, the DAG 1200 is arranged such that there is no way to start atany node and follow a consistently directed sequence of edges thateventually loop back to that same node. A last node (e.g., node “6”),may point to a null value or otherwise indicate an end to the DAG.

Although DAG 1200 depicts six nodes and seven edges, a DAG may includeany suitable number of nodes and directed edges. In some embodiments,each node corresponds to a set of operations (e.g., operations forperforming a task such as deploying and/or booting a resource such asresource A) or a set of capabilities on which a next node of operationsdepends. The directed edges of each DAG define an order by which theseoperations are to be executed and/or a dependency between a subset ofoperations associated with a node and a subset of capabilitiesassociated with an immediately preceding that node.

As a simplistic example, nodes 1, 2, 5, 6, of DAG 1200 are intended todepict nodes corresponding to four separate sets of operations. Based onthe edges depicted in FIG. 1200 , the operations of each node are to beexecuted in the order corresponding to the order of nodes 1, 2, 5, and6. Nodes 3 and 4 are intended to depict nodes that individuallycorrespond with one or more dependencies. By way of example, node 3 maycorrespond to a dependency of operations corresponding to node 5 on acapability associated with a different resource (e.g., resource B).Similarly, node 4 may correspond to a dependency of operationscorresponding to node 5 on a capability associated with a differentresource (e.g., resource C). In some embodiments, different capabilitynodes (e.g., a node identifying a dependency on a particular resource'scapability/capabilities) may be used for different resources, or asingle node may be utilized to specify all dependencies regardless ofhow many resources to which the dependencies refer. Thus, in someembodiments, the dependency corresponding to resource B (e.g.,identified in node 3) and the dependency corresponding to resource C(e.g., identified in node 4) may be combined in a single node.

The DAG 1200 may be traversed in the manner described in more detailwith respect to FIGS. 10-12 to orchestrate the execution of operationsfor booting and/or deploying a resource in a cloud-computing environmentwith respect to one or more dependencies on capabilities of otherresources (or other resources themselves).

FIG. 13 is a flow diagram illustrating an example process 1300 fororchestrating the execution of a task (e.g., deploying a resource) thatincludes a dependency on at least one capability (e.g., a capability ofa different resource), according to at least one embodiment. Asillustrated in FIG. 13 , the process flow 1300 includes a scheduler 1302(e.g. the scheduler 206 of FIG. 2 ), a worker 1304 (e.g. the worker 210of FIG. 2 ), and an IP process 1306 (e.g. the CIOS container 212 of FIG.2 ).

At 1308, the scheduler 1302 may receive a task for deployinginfrastructure resources in a region, and the scheduler 1302 maytransmit data pertaining to the task to the worker 1304. In someembodiments, the scheduler 1302 may instantiate the worker 1304 tohandle deployment of a resource (e.g., a service).

At 1310, the worker 1304 may instantiate IP process 1306 which may beconfigured to execute an instance of a declarative infrastructureprovisioner (e.g., the declarative provisioning tool, Terraform,discussed above).

At 1312, the IP process 1306 may parse a configuration file (e.g., aconfiguration file that includes code segments 1000 and/or 1100 of FIGS.10 and 11 ) associated with the deployment to generate a directedacyclic graph (DAG) for a particular resource. Through parsing theconfiguration, the IP process 1306 (the declarative infrastructureprovisioner) may identify any suitable number of implicit and/orexplicit dependencies on capabilities of other resources. Onceidentified, the IP process 1306 builds a DAG that specifies tasks forbooting and/or deploying a resource with potentially one or more nodesthat correspond to a capability on which the resource depends (e.g., inaccordance with the implicit and/or explicit dependencies identifiedduring the parsing).

At 1314, the IP process 1306 may begin traversing the DAG, executing atleast a portion of the deployment and/or booting of the particularresource as various nodes of the DAG are reached. In accordance with atleast one node of the DAG, any suitable operations may be executed tocause a portion of functionality corresponding to the resource to becomeavailable. It may be that multiple portions of functionalitycorresponding to the resource become available. In some embodiments, theIP process 1306 may transmit to the scheduler 1302 a notificationindicating one or more capabilities of the resource is now available(not depicted). At least one of the nodes of the DAG may correspond to acapability of one or more other resources. When these types of nodes arereached, the IP process 1306 may check to see if the capability isavailable. If so, the IP process 1306 may proceed with its traversal ofthe DAG.

At 1316, the IP process 1306 may reach a node of the DAG thatcorresponds to a one or more capabilities of one or more otherresources. In some embodiments, the IP process 1306 may determine thatat least one capability associated with the node is not yet available.

At 1320, in response to determining at least one capability associatedwith the node is unavailable, the IP process 1306 may transmit data tothe scheduler 1302 indicating the one or more capabilities on which theresource corresponding to the IP process 1306 depends which have beendetermined to be unavailable.

At 1322, the IP process 1306 may exit after potentially storing stateinformation indicating what operations and/or node of the DAG havealready been completed and/or at what particular node of the DAG the IPprocess 1306 was last accessing. The IP process 1306 exits, is killed,is suspended, or otherwise ceases to execute.

At 1324, the scheduler 1302 may store information indicating that theparticular resource was awaiting one or more particular capabilitieswhich are needed for the resource to resume booting and/or fordeployment purposes.

At 1326, the scheduler 1302 may receive one or more notifications thatthe one or more capabilities for which the resource was waiting havebecome available. In some embodiments, the scheduler 1302 may receivevarious notification from other IP processes indicating variouscapabilities of corresponding resources as those capabilities becomeavailable. The scheduler 1302 may maintain one or more records of thevarious capabilities that are available and/or of the variouscapabilities for which resources are currently waiting. The scheduler1302 may identify from the one or more records that the particularcapability/capabilities for which the resource corresponding to IPprocess 1306 is waiting have become available. Accordingly, thescheduler 1302 may proceed to 1328.

At 1328, in response to determining that the capabilities on which theresource corresponding to IP process 1306 depends have become available,the scheduler 1302 may return to step 1308, where it transmits datapertaining to the original task (e.g., deploying the resource) to theworker 1304. In some embodiments, the scheduler 1302 may instantiate anew worker or utilize the previous worker 1304 (as depicted) to continuehandling the task associated with the resource. The worker 1304 mayinstantiate IP process (not depicted) which may be configured to executeparse the configuration file to generate the DAG for the resource. TheIP process may access the stored state information to identify the nodethat was last access in the DAG (e.g., the node corresponding to the oneor more capabilities for which the resource was waiting). Since the oneor more capabilities are now available, the IP process may proceed withits traversal of the DAG in a similar manner as discussed above,executing operations at each node either execute a portion of the taskor check for capabilities on which a next portion of the task depends,until the operations of the end node of the DAG have been completed.

A similar process as discussed above may be performed for every resourceof the task. By way of example, when deploying a system with multipleresources (e.g., multiple services), the process 1300 may be performedon behalf of each resource in order to deploy each resource in thesystem.

FIG. 14 is an example process flow 1400 for executing a release (e.g.,by CIOS), according to at least one embodiment. At event number one, ascheduler 1402 (e.g. the scheduler 206 of FIG. 2 ) may send a task to aworker 1404 (e.g. the worker 210 of FIG. 2 ). The task may includedeploying a computing system or a subset thereof such as deployinginfrastructure resources to a set of execution targets. The task mayinvolve traversing a linked list (e.g., an example of linked list 700 ofFIG. 7 ), a DAG (e.g., DAGS 900 and 1200 of FIGS. 9 and 12 ,respectively), a combination thereof, or any other suitable task fordeploying the computing system. The worker 1404 may receive the taskfrom the scheduler 206. The worker 1404 may be one worker node in afleet of worker nodes. The fleet of worker nodes may include anysuitable number of worker nodes for deploying the computing system. Theworker 1404 may be chosen by the scheduler 1402 based, at least in part,on a capacity of the worker 1404. For example, the scheduler 1402 maychoose to send the task to the worker 1404 if the worker 1404 has themost amount of computing capacity in the fleet of worker nodes.

At event number 2, the worker 1404 may perform one or moreparses/traversals of a configuration file 1406. The configuration file1406 may include instructions for deploying the computing system, andperforming the one or more parses may result in identification ofresources or other capabilities that are desired to be booted orotherwise deployed for deploying the computing system. As a non-limitingexample, the configuration file 1406 may include code segments 600, 800,1000 and 1100 of FIGS. 6, 8, 10, and 11 , respectively.

At event number 3, information from the configuration file 1406 may betransmitted to an IP Process 1408 (e.g. the IP Process 212 of FIG. 2 ).The IP Process 1408 may receive information from the configuration file1406 based on the one or more parses/traversals performed by the worker1404. The information may include a set of capabilities, executiontargets, or any other suitable resources for deploying the computingsystem.

At event number 4, in response to receiving the information from theconfiguration file 1406, the IP Process 1408 may determine an order inwhich capabilities or any other suitable resources for deploying thecomputing system are to be deployed. The IP Process 1408 may generatelinked list of phases 1410 (e.g. an example of linked list 700 of FIG. 7), DAG of execution targets 1412 (e.g. an example of DAG 900 of FIG. 9), DAG of capabilities 1414 (e.g. an example of DAG 1200 of FIG. 12 ),or any other suitable list, graph, or data structure. The linked list1410, DAG of execution targets 1412, and DAG of capabilities 1414(collectively referred to as “the release data structures”) may begenerated in any suitable order.

The release data structures may be utilized to identify and determine anorder for executing tasks of a release. For example, each node of linkedlist of phases 1410 corresponds to a separate instance of a DAG ofexecution targets (e.g., an example of DAG of execution targets 1412),where each node of the DAG of execution targets corresponds to a DAG ofcapabilities (e.g., an example of DAG of capabilities 1414). IP process1408 may begin at a first node of the linked list 1400, to identify acorresponding DAG of execution targets. The first node of the DAG ofexecution targets may be utilized to identify a corresponding DAG ofcapabilities. The tasks associated with that DAG of capabilities may beexecuted in accordance with the DAG of capabilities and upon completion,IP process 1408 may traverse to the next node of the DAG of executiontargets to identify the next corresponding DAG of capabilities. Eachnode of the DAG of execution target may be traversed and, when the taskscorresponding to those nodes are completed, IP process 1408 may thentraverse to the next node of linked list 1400 to identify the nextphase. This process may be repeated any suitable number of times untilall of the tasks associated with each of the execution targetsassociated with the last phase of the release have been completed.

By way of example, at event number 5, a first node of the linked list ofphases 1410 is reached. The IP Process 1408 identify a DAG of executiontargets corresponding to the first node.

At event number 6, the first node of the DAG of execution targets 1412is reached. The DAG of capabilities 1414 may be identified based atleast in part on being associated with the first node of the DAG ofexecution targets 1412.

At event number 7, tasks for a given execution target are executed basedat least in part on traversing the DAG of capabilities 1414. When thosetasks have been completed, the IP process 1408 may traverse to the nextnode of the DAG of execution targets, determine a corresponding DAG ofcapabilities, and execute the tasks according to traversing that DAG ofcapabilities. This process may proceed until the tasks associated withthe last node of the DAG of execution targets 1412 have been executed.The IP process 1408 may then traverse to the next node of the linkedlist of phases 1410. The operations of event number 5-7 may be repeatedany suitable number of times until all of the tasks associated with allof the execution targets associated with the last node of the linkedlist of phases 1410 have been executed. Upon completing a task, anexecution target, and/or a phase, the IP process 1408 may update orcause an update to the UI 500 of FIG. 5 to depict a current state of atask, an execution target, and/or a phase.

At event number 8, the IP Process 1408 transmits a signal to thescheduler 1402 that traversal of the release is complete. The scheduler1402 may receive the signal from the IP Process 1408 and may broadcast anotification that the computing system is ready for use.

FIG. 15 is a flow chart of a process 1500 for deploying a computingsystem using DAGs in CIOS, according to at least one embodiment. Atblock 1502, CIOS may execute instructions for performing one or moreparses of configuration data associated with a deployment of a computingsystem. The configuration data may be included in a configuration file,and in performing the one or more parses of the configuration data, CIOSmay determine a set of tasks to perform to deploy the computing system.Tasks included in the set of tasks may include deploying infrastructureresources at execution targets or any other suitable tasks for deployingthe computing system.

At block 1504, CIOS causes a first DAG (e.g. the DAG 1200 of FIG. 12 )to be generated for deploying resources based on the configuration file.The first DAG may be a DAG of capabilities that may outline a certainorder for capabilities to be booted or otherwise deployed. The first DAGmay include any suitable number of tasks for deploying capabilities andmay include any suitable number of dependencies between the capabilitiesto be deployed.

At block 1506, CIOS generates a second DAG (e.g. the DAG 900 of FIG. 9 )that defines dependencies between execution targets for deployingexecution targets based on the configuration file. The second DAG may aDAG of execution targets that specifies an order to which executiontargets are deployed. The second DAG may include any suitable number ofexecution targets for deploying the computing system and may include anysuitable number of dependencies for deploying execution targets.

At block 1508, CIOS generates a linked list (e.g. the linked list 700 ofFIG. 7 ) that specifies dependencies between phases based on theconfiguration file. The phases may include the first DAGs, the secondDAGs, or a combination thereof, and the linked list may define an orderin which the phases are executed. The phases of the linked list may beexecuted in series and may not include and phases to be executed inparallel. The linked list may include any suitable number of phases fordeploying the computing system.

At block 1510, CIOS deploys the computing system by traversing the firstDAG, the second DAG, and the linked list. CIOS may traverse the linkedlist, and the first DAG and the second DAG may be traversed concurrently(i.e. the first DAG and the second DAG may be included in the linkedlist). A successful traversal of the linked list, the first DAG, and thesecond DAG may result in a successful deployment of the computingsystem.

Illustrative Systems

FIGS. 16-18 illustrate aspects of example environments for implementingaspects of the present disclosure in accordance with variousembodiments. FIG. 16 depicts a simplified diagram of a distributedsystem 1600 for implementing an embodiment of the present disclosure. Inthe illustrated embodiment, the distributed system 1600 includes one ormore client computing devices 1602, 1604, 1606, and 1608, which areconfigured to execute and operate a client application such as a webbrowser, proprietary client (e.g., Oracle Forms), or the like over oneor more network(s) 1610. The server 1612 may be communicatively coupledwith the remote client computing devices 1602, 1604, 1606, and 1608 vianetwork 1610.

In various embodiments, the server 1612 may be adapted to run one ormore services or software applications such as services and applicationsthat provide identity management services. In certain embodiments, theserver 1612 may also provide other services or software applications caninclude non-virtual and virtual environments. In some embodiments, theseservices may be offered as web-based or cloud services or under aSoftware as a Service (SaaS) model to the users of the client computingdevices 1602, 1604, 1606, and/or 1608. Users operating the clientcomputing devices 1602, 1604, 1606, and/or 1608 may in turn utilize oneor more client applications to interact with the server 1612 to utilizethe services provided by these components.

In the configuration depicted in FIG. 16 , the software components 1618,1620 and 1622 of system 1600 are shown as being implemented on theserver 1612. In other embodiments, one or more of the components of thesystem 1600 and/or the services provided by these components may also beimplemented by one or more of the client computing devices 1602, 1604,1606, and/or 1608. Users operating the client computing devices may thenutilize one or more client applications to use the services provided bythese components. These components may be implemented in hardware,firmware, software, or combinations thereof. It should be appreciatedthat various different system configurations are possible, which may bedifferent from distributed system 1600. The embodiment shown in FIG. 16is thus one example of a distributed system for implementing anembodiment system and is not intended to be limiting.

The client computing devices 1602, 1604, 1606, and/or 1608 may includevarious types of computing systems. For example, client device mayinclude portable handheld devices (e.g., an iPhone®, cellular telephone,an iPad®, computing tablet, a personal digital assistant (PDA)) orwearable devices (e.g., a Google Glass® head mounted display), runningsoftware such as Microsoft Windows Mobile®, and/or a variety of mobileoperating systems such as iOS, Windows Phone, Android, BlackBerry 10,Palm OS, and the like. The devices may support various applications suchas various Internet-related apps, e-mail, short message service (SMS)applications, and may use various other communication protocols. Theclient computing devices may also include general purpose personalcomputers including, by way of example, personal computers and/or laptopcomputers running various versions of Microsoft Windows®, AppleMacintosh®, and/or Linux operating systems. The client computing devicescan be workstation computers running any of a variety ofcommercially-available UNIX® or UNIX-like operating systems, includingwithout limitation the variety of GNU/Linux operating systems, such asfor example, Google Chrome OS. Client computing devices may also includeelectronic devices such as a thin-client computer, an Internet-enabledgaming system (e.g., a Microsoft Xbox gaming console with or without aKinect® gesture input device), and/or a personal messaging device,capable of communicating over the network(s) 1610.

Although distributed system 1600 in FIG. 16 is shown with four clientcomputing devices, any number of client computing devices may besupported. Other devices, such as devices with sensors, etc., mayinteract with the server 1612.

The network(s) 1610 in the distributed system 1600 may be any type ofnetwork familiar to those skilled in the art that can support datacommunications using any of a variety of available protocols, includingwithout limitation TCP/IP (transmission control protocol/Internetprotocol), SNA (systems network architecture), IPX (Internet packetexchange), AppleTalk, and the like. Merely by way of example, thenetwork(s) 1610 can be a local area network (LAN), networks based onEthernet, Token-Ring, a wide-area network, the Internet, a virtualnetwork, a virtual private network (VPN), an intranet, an extranet, apublic switched telephone network (PSTN), an infra-red network, awireless network (e.g., a network operating under any of the Instituteof Electrical and Electronics (IEEE) 1002.16 suite of protocols,Bluetooth®, and/or any other wireless protocol), and/or any combinationof these and/or other networks.

The server 1612 may be composed of one or more general purposecomputers, specialized server computers (including, by way of example,PC (personal computer) servers, UNIX® servers, mid-range servers,mainframe computers, rack-mounted servers, etc.), server farms, serverclusters, or any other appropriate arrangement and/or combination. Theserver 1612 can include one or more virtual machines running virtualoperating systems, or other computing architectures involvingvirtualization. One or more flexible pools of logical storage devicescan be virtualized to maintain virtual storage devices for the server.Virtual networks can be controlled by the server 1612 using softwaredefined networking. In various embodiments, the server 1612 may beadapted to run one or more services or software applications describedin the foregoing disclosure. For example, the server 1612 may correspondto a server for performing processing as described above according to anembodiment of the present disclosure.

The server 1612 may run an operating system including any of thosediscussed above, as well as any commercially available server operatingsystem. Server 1612 may also run any of a variety of additional serverapplications and/or mid-tier applications, including HTTP (hypertexttransport protocol) servers, FTP (file transfer protocol) servers, CGI(common gateway interface) servers, JAVA® servers, database servers, andthe like. Example database servers include without limitation thosecommercially available from Oracle, Microsoft, Sybase, IBM(International Business Machines), and the like.

In some implementations, the server 1612 may include one or moreapplications to analyze and consolidate data feeds and/or event updatesreceived from users of the client computing devices 1602, 1604, 1606,and 1608. As an example, data feeds and/or event updates may include,but are not limited to, Twitter® feeds, Facebook® updates or real-timeupdates received from one or more third party information sources andcontinuous data streams, which may include real-time events related tosensor data applications, financial tickers, network performancemeasuring tools (e.g., network monitoring and traffic managementapplications), clickstream analysis tools, automobile trafficmonitoring, and the like. The server 1612 may also include one or moreapplications to display the data feeds and/or real-time events via oneor more display devices of the client computing devices 1602, 1604,1606, and 1608.

The distributed system 1600 may also include one or more databases 1614and 1616. These databases may provide a mechanism for storinginformation such as user identity information, and other informationused by embodiments of the present disclosure. Databases 1614 and 1616may reside in a variety of locations. By way of example, one or more ofdatabases 1614 and 1616 may reside on a non-transitory storage mediumlocal to (and/or resident in) the server 1612. Alternatively, thedatabases 1614 and 1616 may be remote from the server 1612 and incommunication with the server 1612 via a network-based or dedicatedconnection. In one set of embodiments, the databases 1614 and 1616 mayreside in a storage-area network (SAN). Similarly, any necessary filesfor performing the functions attributed to the server 1612 may be storedlocally on the server 1612 and/or remotely, as appropriate. In one setof embodiments, the databases 1614 and 1616 may include relationaldatabases, such as databases provided by Oracle, that are adapted tostore, update, and retrieve data in response to SQL-formatted commands.

FIG. 17 illustrates an example computer system 1700 that may be used toimplement an embodiment of the present disclosure. In some embodiments,computer system 1700 may be used to implement any of the various serversand computer systems described above. As shown in FIG. 17 , computersystem 1700 includes various subsystems including a processing subsystem1704 that communicates with a number of peripheral subsystems via a bussubsystem 1702. These peripheral subsystems may include a processingacceleration unit 1706, an I/O subsystem 1708, a storage subsystem 1718and a communications subsystem 1724. Storage subsystem 1718 may includetangible computer-readable storage media 1722 and a system memory 1710.

Bus subsystem 1702 provides a mechanism for letting the variouscomponents and subsystems of computer system 1700 communicate with eachother as intended. Although bus subsystem 1702 is shown schematically asa single bus, alternative embodiments of the bus subsystem may utilizemultiple buses. Bus subsystem 1702 may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Forexample, such architectures may include an Industry StandardArchitecture (ISA) bus, Micro Channel Architecture (MCA) bus, EnhancedISA (EISA) bus, Video Electronics Standards Association (VESA) localbus, and Peripheral Component Interconnect (PCI) bus, which can beimplemented as a Mezzanine bus manufactured to the IEEE P1386.1standard, and the like.

Processing subsystem 1704 controls the operation of computer system 1700and may comprise one or more processing units 1732, 1734, etc. Aprocessing unit may include be one or more processors, including singlecore or multicore processors, one or more cores of processors, orcombinations thereof. In some embodiments, processing subsystem 1704 caninclude one or more special purpose co-processors such as graphicsprocessors, digital signal processors (DSPs), or the like. In someembodiments, some or all of the processing units of processing subsystem1704 can be implemented using customized circuits, such as applicationspecific integrated circuits (ASICs), or field programmable gate arrays(FPGAs).

In some embodiments, the processing units in processing subsystem 1704can execute instructions stored in system memory 1710 or on computerreadable storage media 1722. In various embodiments, the processingunits can execute a variety of programs or code instructions and canmaintain multiple concurrently executing programs or processes. At anygiven time, some or all of the program code to be executed can beresident in system memory 1710 and/or on computer-readable storage media1710 including potentially on one or more storage devices. Throughsuitable programming, processing subsystem 1704 can provide variousfunctionalities described above for dynamically modifying documents(e.g., webpages) responsive to usage patterns.

In certain embodiments, a processing acceleration unit 1706 may beprovided for performing customized processing or for off-loading some ofthe processing performed by processing subsystem 1704 so as toaccelerate the overall processing performed by computer system 1700.

I/O subsystem 1708 may include devices and mechanisms for inputtinginformation to computer system 1700 and/or for outputting informationfrom or via computer system 1700. In general, use of the term “inputdevice” is intended to include all possible types of devices andmechanisms for inputting information to computer system 1700. Userinterface input devices may include, for example, a keyboard, pointingdevices such as a mouse or trackball, a touchpad or touch screenincorporated into a display, a scroll wheel, a click wheel, a dial, abutton, a switch, a keypad, audio input devices with voice commandrecognition systems, microphones, and other types of input devices. Userinterface input devices may also include motion sensing and/or gesturerecognition devices such as the Microsoft Kinect® motion sensor thatenables users to control and interact with an input device, theMicrosoft Xbox® 360 game controller, devices that provide an interfacefor receiving input using gestures and spoken commands. User interfaceinput devices may also include eye gesture recognition devices such asthe Google Glass® blink detector that detects eye activity (e.g.,“blinking” while taking pictures and/or making a menu selection) fromusers and transforms the eye gestures as input into an input device(e.g., Google Glass®). Additionally, user interface input devices mayinclude voice recognition sensing devices that enable users to interactwith voice recognition systems (e.g., Siri® navigator), through voicecommands.

Other examples of user interface input devices include, withoutlimitation, three dimensional (3D) mice, joysticks or pointing sticks,gamepads and graphic tablets, and audio/visual devices such as speakers,digital cameras, digital camcorders, portable media players, webcams,image scanners, fingerprint scanners, barcode reader 3D scanners, 3Dprinters, laser rangefinders, and eye gaze tracking devices.Additionally, user interface input devices may include, for example,medical imaging input devices such as computed tomography, magneticresonance imaging, position emission tomography, medical ultrasonographydevices. User interface input devices may also include, for example,audio input devices such as MIDI keyboards, digital musical instrumentsand the like.

User interface output devices may include a display subsystem, indicatorlights, or non-visual displays such as audio output devices, etc. Thedisplay subsystem may be a cathode ray tube (CRT), a flat-panel device,such as that using a liquid crystal display (LCD) or plasma display, aprojection device, a touch screen, and the like. In general, use of theterm “output device” is intended to include all possible types ofdevices and mechanisms for outputting information from computer system1700 to a user or other computer. For example, user interface outputdevices may include, without limitation, a variety of display devicesthat visually convey text, graphics and audio/video information such asmonitors, printers, speakers, headphones, automotive navigation systems,plotters, voice output devices, and modems.

Storage subsystem 1718 provides a repository or data store for storinginformation that is used by computer system 1700. Storage subsystem 1718provides a tangible non-transitory computer-readable storage medium forstoring the basic programming and data constructs that provide thefunctionality of some embodiments. Software (programs, code modules,instructions) that when executed by processing subsystem 1704 providethe functionality described above may be stored in storage subsystem1718. The software may be executed by one or more processing units ofprocessing subsystem 1704. Storage subsystem 1718 may also provide arepository for storing data used in accordance with the presentdisclosure.

Storage subsystem 1718 may include one or more non-transitory memorydevices, including volatile and non-volatile memory devices. As shown inFIG. 17 , storage subsystem 1718 includes a system memory 1710 and acomputer-readable storage media 1722. System memory 1710 may include anumber of memories including a volatile main random access memory (RAM)for storage of instructions and data during program execution and anon-volatile read only memory (ROM) or flash memory in which fixedinstructions are stored. In some implementations, a basic input/outputsystem (BIOS), containing the basic routines that help to transferinformation between elements within computer system 1700, such as duringstart-up, may be stored in the ROM. The RAM may contain data and/orprogram modules that are presently being operated and executed byprocessing subsystem 1704. In some implementations, system memory 1710may include multiple different types of memory, such as static randomaccess memory (SRAM) or dynamic random access memory (DRAM).

By way of example, and not limitation, as depicted in FIG. 17 , systemmemory 1710 may store application programs 1712, which may includeclient applications, Web browsers, mid-tier applications, relationaldatabase management systems (RDBMS), etc., program data 1714, and anoperating system 1716. By way of example, operating system 1716 mayinclude various versions of Microsoft Windows®, Apple Macintosh®, and/orLinux operating systems, a variety of commercially-available UNIX® orUNIX-like operating systems (including without limitation the variety ofGNU/Linux operating systems, the Google Chrome® OS, and the like) and/ormobile operating systems such as iOS, Windows® Phone, Android® OS,BlackBerry® 10 OS, and Palm® OS operating systems.

Computer-readable storage media 1722 may store programming and dataconstructs that provide the functionality of some embodiments. Software(programs, code modules, instructions) that when executed by processingsubsystem 1704 a processor provide the functionality described above maybe stored in storage subsystem 1718. By way of example,computer-readable storage media 1722 may include non-volatile memorysuch as a hard disk drive, a magnetic disk drive, an optical disk drivesuch as a CD ROM, DVD, a Blu-Ray® disk, or other optical media.Computer-readable storage media 1722 may include, but is not limited to,Zip® drives, flash memory cards, universal serial bus (USB) flashdrives, secure digital (SD) cards, DVD disks, digital video tape, andthe like. Computer-readable storage media 1722 may also include,solid-state drives (SSD) based on non-volatile memory such asflash-memory based SSDs, enterprise flash drives, solid state ROM, andthe like, SSDs based on volatile memory such as solid state RAM, dynamicRAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, andhybrid SSDs that use a combination of DRAM and flash memory based SSDs.Computer-readable media 1722 may provide storage of computer-readableinstructions, data structures, program modules, and other data forcomputer system 1700.

In certain embodiments, storage subsystem 1700 may also include acomputer-readable storage media reader 1720 that can further beconnected to computer-readable storage media 1722. Together and,optionally, in combination with system memory 1710, computer-readablestorage media 1722 may comprehensively represent remote, local, fixed,and/or removable storage devices plus storage media for storingcomputer-readable information.

In certain embodiments, computer system 1700 may provide support forexecuting one or more virtual machines. Computer system 1700 may executea program such as a hypervisor for facilitating the configuring andmanaging of the virtual machines. Each virtual machine may be allocatedmemory, compute (e.g., processors, cores), I/O, and networkingresources. Each virtual machine may run its own operating system, whichmay be the same as or different from the operating systems executed byother virtual machines executed by computer system 1700. Accordingly,multiple operating systems may potentially be run concurrently bycomputer system 1700. Each virtual machine generally runs independentlyof the other virtual machines.

Communications subsystem 1724 provides an interface to other computersystems and networks. Communications subsystem 1724 serves as aninterface for receiving data from and transmitting data to other systemsfrom computer system 1700. For example, communications subsystem 1724may enable computer system 1700 to establish a communication channel toone or more client devices via the Internet for receiving and sendinginformation from and to the client devices. Additionally, communicationsubsystem 1724 may be used to communicate notifications of successfullogins or notifications to re-enter a password from the privilegedaccount manager to the requesting users.

Communication subsystem 1724 may support both wired and/or wirelesscommunication protocols. For example, in certain embodiments,communications subsystem 1724 may include radio frequency (RF)transceiver components for accessing wireless voice and/or data networks(e.g., using cellular telephone technology, advanced data networktechnology, such as 3G, 4G or EDGE (enhanced data rates for globalevolution), WiFi (IEEE 802.11 family standards, or other mobilecommunication technologies, or any combination thereof), globalpositioning system (GPS) receiver components, and/or other components.In some embodiments communications subsystem 1724 can provide wirednetwork connectivity (e.g., Ethernet) in addition to or instead of awireless interface.

Communication subsystem 1724 can receive and transmit data in variousforms. For example, in some embodiments, communications subsystem 1724may receive input communication in the form of structured and/orunstructured data feeds 1726, event streams 1728, event updates 1730,and the like. For example, communications subsystem 1724 may beconfigured to receive (or send) data feeds 1726 in real-time from usersof social media networks and/or other communication services such asTwitter® feeds, Facebook® updates, web feeds such as Rich Site Summary(RSS) feeds, and/or real-time updates from one or more third partyinformation sources.

In certain embodiments, communications subsystem 1724 may be configuredto receive data in the form of continuous data streams, which mayinclude event streams 1728 of real-time events and/or event updates1730, that may be continuous or unbounded in nature with no explicitend. Examples of applications that generate continuous data may include,for example, sensor data applications, financial tickers, networkperformance measuring tools (e.g. network monitoring and trafficmanagement applications), clickstream analysis tools, automobile trafficmonitoring, and the like.

Communications subsystem 1724 may also be configured to output thestructured and/or unstructured data feeds 1726, event streams 1728,event updates 1730, and the like to one or more databases that may be incommunication with one or more streaming data source computers coupledto computer system 1700.

Computer system 1700 can be one of various types, including a handheldportable device (e.g., an iPhone® cellular phone, an iPad® computingtablet, a PDA), a wearable device (e.g., a Google Glass® head mounteddisplay), a personal computer, a workstation, a mainframe, a kiosk, aserver rack, or any other data processing system.

Due to the ever-changing nature of computers and networks, thedescription of computer system 1700 depicted in FIG. 17 is intended onlyas a specific example. Many other configurations having more or fewercomponents than the system depicted in FIG. 17 are possible. Based onthe disclosure and teachings provided herein, a person of ordinary skillin the art will appreciate other ways and/or methods to implement thevarious embodiments.

Systems depicted in some of the figures may be provided in variousconfigurations. In some embodiments, the systems may be configured as adistributed system where one or more components of the system aredistributed across one or more networks in one or more cloudinfrastructure systems.

A cloud infrastructure system is a collection of one or more servercomputing devices, network devices, and/or storage devices. Theseresources may be divided by cloud services providers and allotted to itscustomers in some manner. For example, a cloud services provider, suchas Oracle Corporation of Redwood Shores, Calif., may offer various typesof cloud services including but not limited to one or more servicesprovided under Software as a Service (SaaS) category, services providedunder Platform as a Service (PaaS) category, services provided underInfrastructure as a Service (IaaS) category, or other categories ofservices including hybrid services. Examples of SaaS services include,without limitation, capabilities to build and deliver a suite ofon-demand applications such as Oracle Fusion applications. SaaS servicesenable customers to utilize applications executing on the cloudinfrastructure system without the need for customers to purchasesoftware for the applications. Examples of PaaS services include withoutlimitation services that enable organizations (such as Oracle) toconsolidate existing applications on a shared, common architecture, aswell as the ability to build new applications that leverage the sharedservices provided by the platform such as Oracle Java Cloud Service(JCS), Oracle Database Cloud Service (DBCS), and others. IaaS servicesmay facilitate the management and control of the underlying computingresources, such as storage, networks, and other fundamental computingresources for customers utilizing services provided by the SaaS platformand the PaaS platform.

FIG. 18 is a simplified block diagram of one or more components of asystem environment 1800 by which services provided by one or morecomponents of an embodiment system may be offered as cloud services, inaccordance with an embodiment of the present disclosure. In theillustrated embodiment, system environment 1800 includes one or moreclient computing devices 1804, 1806, and 1808 that may be used by usersto interact with a cloud infrastructure system 1802 that provides cloudservices. The client computing devices may be configured to operate aclient application such as a web browser, a proprietary clientapplication (e.g., Oracle Forms), or some other application, which maybe used by a user of the client computing device to interact with cloudinfrastructure system 1802 to use services provided by cloudinfrastructure system 1802.

It should be appreciated that cloud infrastructure system 1802 depictedin the figure may have other components than those depicted. Further,the embodiment shown in the figure is only one example of a cloudinfrastructure system that may incorporate an embodiment of thedisclosure. In some other embodiments, cloud infrastructure system 1802may have more or fewer components than shown in the figure, may combinetwo or more components, or may have a different configuration orarrangement of components.

Client computing devices 1804, 1806, and 1808 may be devices similar tothose described above for 1602, 1604, 1606, and 1608.

Although example system environment 1800 is shown with three clientcomputing devices, any number of client computing devices may besupported. Other devices such as devices with sensors, etc. may interactwith cloud infrastructure system 1802.

Network(s) 1810 may facilitate communications and exchange of databetween clients 1804, 1806, and 1808 and cloud infrastructure system1802. Each network may be any type of network familiar to those skilledin the art that can support data communications using any of a varietyof commercially-available protocols, including those described above fornetwork(s) 1810.

Cloud infrastructure system 1802 may comprise one or more computersand/or servers that may include those described above for server 1812.

In certain embodiments, services provided by the cloud infrastructuresystem may include a host of services that are made available to usersof the cloud infrastructure system on demand, such as online datastorage and backup solutions, Web-based e-mail services, hosted officesuites and document collaboration services, database processing, managedtechnical support services, and the like. Services provided by the cloudinfrastructure system can dynamically scale to meet the needs of itsusers. A specific instantiation of a service provided by cloudinfrastructure system is referred to herein as a “service instance.” Ingeneral, any service made available to a user via a communicationnetwork, such as the Internet, from a cloud service provider's system isreferred to as a “cloud service.” In a public cloud environment, serversand systems that make up the cloud service provider's system aredifferent from the customer's own on-premises servers and systems. Forexample, a cloud service provider's system may host an application, anda user may, via a communication network such as the Internet, on demand,order and use the application.

In some examples, a service in a computer network cloud infrastructuremay include protected computer network access to storage, a hosteddatabase, a hosted web server, a software application, or other serviceprovided by a cloud vendor to a user, or as otherwise known in the art.For example, a service can include password-protected access to remotestorage on the cloud through the Internet. As another example, a servicecan include a web service-based hosted relational database and ascript-language middleware engine for private use by a networkeddeveloper. As another example, a service can include access to an emailsoftware application hosted on a cloud vendor's web site.

In certain embodiments, cloud infrastructure system 1802 may include asuite of applications, middleware, and database service offerings thatare delivered to a customer in a self-service, subscription-based,elastically scalable, reliable, highly available, and secure manner. Anexample of such a cloud infrastructure system is the Oracle Public Cloudprovided by the present assignee.

In various embodiments, cloud infrastructure system 1802 may be adaptedto automatically provision, manage and track a customer's subscriptionto services offered by cloud infrastructure system 1802. Cloudinfrastructure system 1802 may provide the cloud services via differentdeployment models. For example, services may be provided under a publiccloud model in which cloud infrastructure system 1802 is owned by anorganization selling cloud services (e.g., owned by Oracle) and theservices are made available to the general public or different industryenterprises. As another example, services may be provided under aprivate cloud model in which cloud infrastructure system 1802 isoperated solely for a single organization and may provide services forone or more entities within the organization. The cloud services mayalso be provided under a community cloud model in which cloudinfrastructure system 1802 and the services provided by cloudinfrastructure system 1802 are shared by several organizations in arelated community. The cloud services may also be provided under ahybrid cloud model, which is a combination of two or more differentmodels.

In some embodiments, the services provided by cloud infrastructuresystem 1802 may include one or more services provided under Software asa Service (SaaS) category, Platform as a Service (PaaS) category,Infrastructure as a Service (IaaS) category, or other categories ofservices including hybrid services. A customer, via a subscriptionorder, may order one or more services provided by cloud infrastructuresystem 1802. Cloud infrastructure system 1802 then performs processingto provide the services in the customer's subscription order.

In some embodiments, the services provided by cloud infrastructuresystem 1802 may include, without limitation, application services,platform services and infrastructure services. In some examples,application services may be provided by the cloud infrastructure systemvia a SaaS platform. The SaaS platform may be configured to providecloud services that fall under the SaaS category. For example, the SaaSplatform may provide capabilities to build and deliver a suite ofon-demand applications on an integrated development and deploymentplatform. The SaaS platform may manage and control the underlyingsoftware and infrastructure for providing the SaaS services. Byutilizing the services provided by the SaaS platform, customers canutilize applications executing on the cloud infrastructure system.Customers can acquire the application services without the need forcustomers to purchase separate licenses and support. Various differentSaaS services may be provided. Examples include, without limitation,services that provide solutions for sales performance management,enterprise integration, and business flexibility for largeorganizations.

In some embodiments, platform services may be provided by the cloudinfrastructure system via a PaaS platform. The PaaS platform may beconfigured to provide cloud services that fall under the PaaS category.Examples of platform services may include without limitation servicesthat enable organizations (such as Oracle) to consolidate existingapplications on a shared, common architecture, as well as the ability tobuild new applications that leverage the shared services provided by theplatform. The PaaS platform may manage and control the underlyingsoftware and infrastructure for providing the PaaS services. Customerscan acquire the PaaS services provided by the cloud infrastructuresystem without the need for customers to purchase separate licenses andsupport. Examples of platform services include, without limitation,Oracle Java Cloud Service (JCS), Oracle Database Cloud Service (DBCS),and others.

By utilizing the services provided by the PaaS platform, customers canemploy programming languages and tools supported by the cloudinfrastructure system and also control the deployed services. In someembodiments, platform services provided by the cloud infrastructuresystem may include database cloud services, middleware cloud services(e.g., Oracle Fusion Middleware services), and Java cloud services. Inone embodiment, database cloud services may support shared servicedeployment models that enable organizations to pool database resourcesand offer customers a Database as a Service in the form of a databasecloud. Middleware cloud services may provide a platform for customers todevelop and deploy various business applications, and Java cloudservices may provide a platform for customers to deploy Javaapplications, in the cloud infrastructure system.

Various different infrastructure services may be provided by an IaaSplatform in the cloud infrastructure system. The infrastructure servicesfacilitate the management and control of the underlying computingresources, such as storage, networks, and other fundamental computingresources for customers utilizing services provided by the SaaS platformand the PaaS platform.

In certain embodiments, cloud infrastructure system 1802 may alsoinclude infrastructure resources 1830 for providing the resources usedto provide various services to customers of the cloud infrastructuresystem. In one embodiment, infrastructure resources 1830 may includepre-integrated and optimized combinations of hardware, such as servers,storage, and networking resources to execute the services provided bythe PaaS platform and the SaaS platform.

In some embodiments, resources in cloud infrastructure system 1802 maybe shared by multiple users and dynamically re-allocated per demand.Additionally, resources may be allocated to users in different timezones. For example, cloud infrastructure system 1830 may enable a firstset of users in a first time zone to utilize resources of the cloudinfrastructure system for a specified number of hours and then enablethe re-allocation of the same resources to another set of users locatedin a different time zone, thereby maximizing the utilization ofresources.

In certain embodiments, a number of internal shared services 1832 may beprovided that are shared by different components or modules of cloudinfrastructure system 1802 and by the services provided by cloudinfrastructure system 1802. These internal shared services may include,without limitation, a security and identity service, an integrationservice, an enterprise repository service, an enterprise managerservice, a virus scanning and white list service, a high availability,backup and recovery service, service for enabling cloud support, anemail service, a notification service, a file transfer service, and thelike.

In certain embodiments, cloud infrastructure system 1802 may providecomprehensive management of cloud services (e.g., SaaS, PaaS, and IaaSservices) in the cloud infrastructure system. In one embodiment, cloudmanagement functionality may include capabilities for provisioning,managing and tracking a customer's subscription received by cloudinfrastructure system 1802, and the like.

In one embodiment, as depicted in the figure, cloud managementfunctionality may be provided by one or more modules, such as an ordermanagement module 1820, an order orchestration module 1822, an orderprovisioning module 1824, an order management and monitoring module1826, and an identity management module 1828. These modules may includeor be provided using one or more computers and/or servers, which may begeneral purpose computers, specialized server computers, server farms,server clusters, or any other appropriate arrangement and/orcombination.

In example operation 1834, a customer using a client device, such asclient device 1804, 1806 or 1808, may interact with cloud infrastructuresystem 1802 by requesting one or more services provided by cloudinfrastructure system 1802 and placing an order for a subscription forone or more services offered by cloud infrastructure system 1802. Incertain embodiments, the customer may access a cloud User Interface(UI), cloud UI 1812, cloud UI 1814 and/or cloud UI 1816 and place asubscription order via these UIs. The order information received bycloud infrastructure system 1802 in response to the customer placing anorder may include information identifying the customer and one or moreservices offered by the cloud infrastructure system 1802 that thecustomer intends to subscribe to.

After an order has been placed by the customer, the order information isreceived via the cloud UIs, 1812, 1814 and/or 1816.

At operation 1836, the order is stored in order database 1818. Orderdatabase 1818 can be one of several databases operated by cloudinfrastructure system 1818 and operated in conjunction with other systemelements.

At operation 1838, the order information is forwarded to an ordermanagement module 1820. In some instances, order management module 1820may be configured to perform billing and accounting functions related tothe order, such as verifying the order, and upon verification, bookingthe order.

At operation 1840, information regarding the order is communicated to anorder orchestration module 1822. Order orchestration module 1822 mayutilize the order information to orchestrate the provisioning ofservices and resources for the order placed by the customer. In someinstances, order orchestration module 1822 may orchestrate theprovisioning of resources to support the subscribed services using theservices of order provisioning module 1824.

In certain embodiments, order orchestration module 1822 enables themanagement of business processes associated with each order and appliesbusiness logic to determine whether an order should proceed toprovisioning. At operation 1842, upon receiving an order for a newsubscription, order orchestration module 1822 sends a request to orderprovisioning module 1824 to allocate resources and configure thoseresources needed to fulfill the subscription order. Order provisioningmodule 1824 enables the allocation of resources for the services orderedby the customer. Order provisioning module 1824 provides a level ofabstraction between the cloud services provided by cloud infrastructuresystem 1800 and the physical implementation layer that is used toprovision the resources for providing the requested services. Orderorchestration module 1822 may thus be isolated from implementationdetails, such as whether or not services and resources are actuallyprovisioned on the fly or pre-provisioned and only allocated/assignedupon request.

At operation 1844, once the services and resources are provisioned, anotification of the provided service may be sent to customers on clientdevices 1804, 1806 and/or 1808 by order provisioning module 1824 ofcloud infrastructure system 1802. At operation 1846, the customer'ssubscription order may be managed and tracked by an order management andmonitoring module 1826. In some instances, order management andmonitoring module 1826 may be configured to collect usage statistics forthe services in the subscription order, such as the amount of storageused, the amount data transferred, the number of users, and the amountof system up time and system down time.

In certain embodiments, cloud infrastructure system 1800 may include anidentity management module 1828. Identity management module 1828 may beconfigured to provide identity services, such as access management andauthorization services in cloud infrastructure system 1800. In someembodiments, identity management module 1828 may control informationabout customers who wish to utilize the services provided by cloudinfrastructure system 1802. Such information can include informationthat authenticates the identities of such customers and information thatdescribes which actions those customers are authorized to performrelative to various system resources (e.g., files, directories,applications, communication ports, memory segments, etc.). Identitymanagement module 1828 may also include the management of descriptiveinformation about each customer and about how and by whom thatdescriptive information can be accessed and modified.

Although specific embodiments of the disclosure have been described,various modifications, alterations, alternative constructions, andequivalents are also encompassed within the scope of the disclosure.Embodiments of the present disclosure are not restricted to operationwithin certain specific data processing environments, but are free tooperate within a plurality of data processing environments.Additionally, although embodiments of the present disclosure have beendescribed using a particular series of transactions and steps, it shouldbe apparent to those skilled in the art that the scope of the presentdisclosure is not limited to the described series of transactions andsteps. Various features and aspects of the above-described embodimentsmay be used individually or jointly.

Further, while embodiments of the present disclosure have been describedusing a particular combination of hardware and software, it should berecognized that other combinations of hardware and software are alsowithin the scope of the present disclosure. Embodiments of the presentdisclosure may be implemented only in hardware, or only in software, orusing combinations thereof. The various processes described herein canbe implemented on the same processor or different processors in anycombination. Accordingly, where components or modules are described asbeing configured to perform certain operations, such configuration canbe accomplished, e.g., by designing electronic circuits to perform theoperation, by programming programmable electronic circuits (such asmicroprocessors) to perform the operation, or any combination thereof.Processes can communicate using a variety of techniques including butnot limited to conventional techniques for inter process communication,and different pairs of processes may use different techniques, or thesame pair of processes may use different techniques at different times.

The specification and drawings are, accordingly, to be regarded in anillustrative rather than a restrictive sense. It will, however, beevident that additions, subtractions, deletions, and other modificationsand changes may be made thereunto without departing from the broaderspirit and scope as set forth in the claims. Thus, although specificdisclosure embodiments have been described, these are not intended to belimiting. Various modifications and equivalents are within the scope ofthe following claims.

What is claimed is:
 1. A computer-implemented method, comprising:executing a cloud infrastructure orchestration service configured toprovision infrastructure resources and to deploy services to theinfrastructure resources based at least in part on a set ofconfiguration files that describe, via declarative instructions, theinfrastructure resources to be provisioned and the services to bedeployed; executing, by the cloud infrastructure orchestration service,instructions to perform one or more parses of one or more configurationfiles associated with deploying a plurality of services to a pluralityof execution targets; causing, by the cloud infrastructure orchestrationservice, a first directed acyclic graph (DAG) to be generated, the firstDAG being utilized for deploying the plurality of services to anexecution target based at least in part on performing the one or moreparses, the first DAG indicating dependencies between tasks associatedwith deploying the plurality of services to the execution target;generating, by the cloud infrastructure orchestration service, a secondDAG for deploying the plurality of services to the plurality ofexecution targets based at least in part on performing the one or moreparses, the plurality of execution targets comprising the executiontarget, the second DAG specifying dependencies between associated withdifferent deployments of the plurality of services to each of theplurality of execution targets; generating, by the cloud infrastructureorchestration service, a linked list data structure based at least inpart on performing the one or more parses, the linked list datastructure specifying dependencies between a plurality of deploymentphases, each phase being associated with a different set of executiontargets to which the plurality of services are to be deployed; anddeploying, by the cloud infrastructure orchestration service, theplurality of services to the plurality of execution targets based atleast in part on traversing the linked list data structure, the secondDAG, and the first DAG.
 2. The computer-implemented method of claim 1,wherein the first DAG specifies a dependency of a first resource on acapability of a second resource, and wherein the first resource and thesecond resource are each a respective service of the plurality ofservices, and wherein the capability is a portion of functionality ofthe second resource.
 3. The computer-implemented method of claim 1,wherein at least one node of the second DAG references a node of thefirst DAG.
 4. The computer-implemented method of claim 1, wherein a nodeof the linked list data structure references at least one node of thesecond DAG.
 5. The computer-implemented method of claim 1, whereinexecuting the instructions for performing the one or more parses of theone or more configuration files comprises: detecting a first dependencyvia an explicit statement provided in the one or more configurationfiles; or detecting a second dependency based at least in part onidentifying an implicit dependency provided in the one or moreconfiguration files.
 6. The computer-implemented method of claim 1,wherein the one or more configuration files indicate, via one or moredependencies, an order for executing infrastructure deploymentoperations for deploying a plurality of resources.
 7. Thecomputer-implemented method of claim 1, wherein the dependencies aredefined utilizing declarative statements.
 8. The computer-implementedmethod of claim 1, wherein traversing the linked list data structure,the second DAG, and the first DAG, further comprises: traversing to afirst node of the linked list data structure; identifying the second DAGfrom the first node of the linked list data structure; traversing to afirst node of the second DAG; identifying the first DAG from the firstnode of the second DAG; traversing to a first node of the first DAG; anddeploying at least a portion of a first service of the plurality ofservices based at least in part on traversing to a first node of thelinked list data structure, traversing to the first node of the secondDAG, and traversing to the first node of the first DAG.
 9. Thecomputer-implemented method of claim 8, further comprising: identifying,based at least in part on traversing to a second node of the first DAG,that a portion of a second service to be deployed is dependent on acapability of a third service being available; identifying that thecapability of the third service is unavailable; and delaying deploymentof the portion of the second service until the capability of the thirdservices is available.
 10. The computer-implemented method of claim 9,wherein delaying the deployment of the portion of the second servicefurther comprises: providing, to a computing component associated withthe cloud infrastructure orchestration service, an indication of thecapability on which the portion of the second service is dependent; andresuming traversing the first DAG from the second node of the first DAGbased at least in part on receiving, by the computing component, dataindicating that the capability is available.
 11. Thecomputer-implemented method of claim 10, further comprising: executingoperations corresponding to last end node of the first DAG; traversingto a second node of the second DAG, the first node of the second DAGcorresponding to a first deployment of the plurality of services and thesecond node of the second DAG corresponding to a second deployment ofthe plurality of services; identifying the first DAG as being associatedwith the second node; and deploying the plurality of services as part ofthe second deployment based at least in part on traversing the firstDAG.
 12. The computer-implemented method of claim 11, furthercomprising: executing operations corresponding to a last end node of thesecond DAG; traversing to a second node of the linked list datastructure, the first node of the linked list data structurecorresponding to a first set of execution targets to which the pluralityof services are to be deployed, the second node of the linked list datastructure corresponding to a second set of execution targets to whichthe plurality of services are to be deployed; identifying the second DAGas being associated with the second node; and deploying the plurality ofservices to each of the second set of execution targets based at leastin part on traversing the second DAG.
 13. A system, comprising: one ormore processors; and one or more memories storing computer-executableinstructions that, when executed by the one or more processors,configure the one or more processors to: execute a cloud infrastructureorchestration service configured to provision infrastructure resourcesand to deploy services to the infrastructure resources based at least inpart on a set of configuration files that describe, via declarativeinstructions, the infrastructure resources to be provisioned and theservices to be deployed; execute, by the cloud infrastructureorchestration service, instructions to perform one or more parses of oneor more configuration files associated with deploying a plurality ofservices to a plurality of execution targets; cause, by the cloudinfrastructure orchestration service, a first DAG to be generated, thefirst DAG being utilized for deploying the plurality of services to anexecution target based at least in part on performing the one or moreparses, the first DAG indicating dependencies between tasks associatedwith deploying the plurality of services to the execution target;generate, by the cloud infrastructure orchestration service, a secondDAG for deploying the plurality of services to the plurality ofexecution targets based at least in part on performing the one or moreparses, the plurality of execution targets comprising the executiontarget, the second DAG specifying dependencies associated with differentdeployments of the plurality of services to each of the plurality ofexecution targets; generate, by the cloud infrastructure orchestrationservice, a linked list data structure based at least in part onperforming the one or more parses, the linked list data structurespecifying dependencies between a plurality of deployment phases, eachphase being associated with a different set of execution targets towhich the plurality of services are to be deployed; and deploy, by thecloud infrastructure orchestration service, the plurality of services tothe plurality of execution targets based at least in part on traversingthe linked list data structure, the second DAG, and the first DAG. 14.The system of claim 13, wherein the first DAG specifies a dependency ofa first resource on a capability of a second resource, and wherein thefirst resource and the second resource are each a respective service ofthe plurality of computing, and wherein the capability is a portion offunctionality of the second resource.
 15. The system of claim 13,wherein at least one node of the second DAG references a first node ofthe first DAG, and wherein a second node of the linked list datastructure references at least one node of the second DAG.
 16. The systemof claim 13, wherein the one or more configuration files indicate, viaone or more dependencies, an order for executing infrastructuredeployment operations for deploying a plurality of resources, whereinthe one or more dependencies are defined utilizing declarativestatements, and wherein executing the instructions for performing theone or more parses of the one or more configuration files comprises:detecting a first dependency via an explicit statement provided in theone or more configuration files; or detecting a second dependency basedat least in part on identifying an implicit dependency provided in theone or more configuration files.
 17. A non-transitory computer-readablestorage medium storing computer-executable instructions that, whenexecuted by one or more processors, cause the one or more processors toperform operations comprising: executing a cloud infrastructureorchestration service configured to provision infrastructure resourcesand to deploy services to the infrastructure resources based at least inpart on a set of configuration files that describe, via declarativeinstructions, the infrastructure resources to be provisioned and theservices to be deployed; executing, by the cloud infrastructureorchestration service, instructions to perform one or more parses of oneor more configuration files associated with deploying a plurality ofservices to a plurality of execution targets; causing, by the cloudinfrastructure orchestration service, a first DAG to be generated, thefirst DAG being utilized for deploying the plurality of services to anexecution target based at least in part on performing the one or moreparses, the first DAG indicating dependencies between tasks associatedwith deploying the plurality of services to the execution target;generating, by the cloud infrastructure orchestration service, a secondDAG for deploying the plurality of services to the plurality ofexecution targets based at least in part on performing the one or moreparses, the plurality of execution targets comprising the executiontarget, the second DAG specifying dependencies associated with differentdeployments of the plurality of services to each of the plurality ofexecution targets; generating, by the cloud infrastructure orchestrationservice, a linked list data structure based at least in part onperforming the one or more parses, the linked list data structurespecifying dependencies between a plurality of deployment phases, eachphase being associated with a different set of execution targets towhich the plurality of services are to be deployed; and deploying, bythe cloud infrastructure orchestration service, the plurality ofservices to the plurality of execution targets based at least in part ontraversing the linked list data structure, the second DAG, and the firstDAG.
 18. The computer-readable storage medium of claim 17, wherein thefirst DAG specifies a dependency of a first resource on a capability ofa second resource, and wherein the first resource and second resourceare each a respective service of the plurality of services, and whereinthe capability is a portion of functionality of the second resource. 19.The computer-readable storage medium of claim 17, wherein at least onenode of the second DAG references a first node of the first DAG, andwherein a second node of the linked list data structure references atleast one node of the second DAG.
 20. The computer-readable storagemedium of claim 17, wherein executing the instructions for performingthe one or more parses of the one or more configuration files comprises:detecting a first dependency via an explicit statement provided in theone or more configuration files; or detecting a second dependency basedat least in part on identifying an implicit dependency provided in theone or more configuration files.